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AAAI Technical Track on Application Domains

The Undergraduate Games Corpus: A Dataset for Machine Perception of Interactive Media

Efficient Poverty Mapping from High Resolution Remote Sensing Images

Optimal Kidney Exchange with Immunosuppressants

TreeCaps: Tree-Based Capsule Networks for Source Code Processing

A Bottom-Up DAG Structure Extraction Model for Math Word Problems

Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring

Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks

Differentially Private Link Prediction with Protected Connections

Graph Neural Network to Dilute Outliers for Refactoring Monolith Application

KAN: Knowledge-aware Attention Network for Fake News Detection

When Hashing Met Matching: Efficient Spatio-Temporal Search for Ridesharing

Gene Regulatory Network Inference using 3D Convolutional Neural Network

Universal Trading for Order Execution with Oracle Policy Distillation

Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization

ECG ODE-GAN: Learning Ordinary Differential Equations of ECG Dynamics via Generative Adversarial Learning

Towered Actor Critic For Handling Multiple Action Types In Reinforcement Learning For Drug Discovery

Hierarchical Graph Convolution Network for Traffic Forecasting

Automated Lay Language Summarization of Biomedical Scientific Reviews

Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

Modeling the Compatibility of Stem Tracks to Generate Music Mashups

SDGNN: Learning Node Representation for Signed Directed Networks

The Causal Learning of Retail Delinquency

Deep Portfolio Optimization via Distributional Prediction of Residual Factors

Complex Coordinate-Based Meta-Analysis with Probabilistic Programming

Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce

Estimating Calibrated Individualized Survival Curves with Deep Learning

Deep Contextual Clinical Prediction with Reverse Distillation

Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search

Predicting Livelihood Indicators from Community-Generated Street-Level Imagery

Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws

Two-Stream Convolution Augmented Transformer for Human Activity Recognition

Traffic Flow Prediction with Vehicle Trajectories

RevMan: Revenue-aware Multi-task Online Insurance Recommendation

MeInGame: Create a Game Character Face from a Single Portrait

Community-Aware Multi-Task Transportation Demand Prediction

Asynchronous Stochastic Gradient Descent for Extreme-Scale Recommender Systems

In-game Residential Home Planning via Visual Context-aware Global Relation Learning

Relational Classification of Biological Cells in Microscopy Images

Deep Style Transfer for Line Drawings

RNA Secondary Structure Representation Network for RNA-proteins Binding Prediction

PANTHER: Pathway Augmented Nonnegative Tensor Factorization for HighER-order Feature Learning

Programmatic Strategies for Real-Time Strategy Games

Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning

Low-Rank Registration Based Manifolds for Convection-Dominated PDEs

Symbolic Music Generation with Transformer-GANs

Bringing UMAP Closer to the Speed of Light with GPU Acceleration

Deep Just-In-Time Inconsistency Detection Between Comments and Source Code

XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors

Pragmatic Code Autocomplete

RareBERT: Transformer Architecture for Rare Disease Patient Identification using Administrative Claims

Queue-Learning: A Reinforcement Learning Approach for Providing Quality of Service

Research Reproducibility as a Survival Analysis

DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis

CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG

Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach

Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting Agent

StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling

Integrating Static and Dynamic Data for Improved Prediction of Cognitive Declines Using Augmented Genotype-Phenotype Representations

GTA: Graph Truncated Attention for Retrosynthesis

Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models

The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network

Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multi-modal Data

Oral-3D: Reconstructing the 3D Structure of Oral Cavity from Panoramic X-ray

Traffic Shaping in E-Commercial Search Engine: Multi-Objective Online Welfare Maximization

Fully Exploiting Cascade Graphs for Real-time Forwarding Prediction

A Hierarchical Approach to Multi-Event Survival Analysis

DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations

Sketch Generation with Drawing Process Guided by Vector Flow and Grayscale

PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning

Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management

Alternative Baselines for Low-Shot 3D Medical Image Segmentation---An Atlas Perspective

DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series

Automated Symbolic Law Discovery: A Computer Vision Approach

Hierarchically and Cooperatively Learning Traffic Signal Control

Deep Partial Rank Aggregation for Personalized Attributes

Towards Efficient Selection of Activity Trajectories based on Diversity and Coverage

Minimizing Labeling Cost for Nuclei Instance Segmentation and Classification with Cross-domain Images and Weak Labels

Bigram and Unigram Based Text Attack via Adaptive Monotonic Heuristic Search

GRASP: Generic Framework for Health Status Representation Learning Based on Incorporating Knowledge from Similar Patients

Window Loss for Bone Fracture Detection and Localization in X-ray Images with Point-based Annotation

A Spatial Regulated Patch-Wise Approach for Cervical Dysplasia Diagnosis

Online 3D Bin Packing with Constrained Deep Reinforcement Learning

DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems

Towards Balanced Defect Prediction with Better Information Propagation

Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification

AAAI Technical Track on Cognitive Modeling and Cognitive Systems

Probabilistic Programming Bots in Intuitive Physics Game Play

Model-Agnostic Fits for Understanding Information Seeking Patterns in Humans

Apparently Irrational Choice as Optimal Sequential Decision Making

Visual Relation Detection using Hybrid Analogical Learning

Neural Analogical Matching

Interpretable Self-Supervised Facial Micro-Expression Learning to Predict Cognitive State and Neurological Disorders

Quantum Cognitively Motivated Decision Fusion for Video Sentiment Analysis

Towards a Better Understanding of VR Sickness: Physical Symptom Prediction for VR Contents

PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception

Riemannian Embedding Banks for Common Spatial Patterns with EEG-based SPD Neural Networks

Plug-and-Play Domain Adaptation for Cross-Subject EEG-based Emotion Recognition

AAAI Technical Track on Computer Vision I

Localization in the Crowd with Topological Constraints

Deep Event Stereo Leveraged by Event-to-Image Translation

Optical Flow Estimation from a Single Motion-blurred Image

Motion-blurred Video Interpolation and Extrapolation

Disentangled Multi-Relational Graph Convolutional Network for Pedestrian Trajectory Prediction

Dense Events Grounding in Video

Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification

Appearance-Motion Memory Consistency Network for Video Anomaly Detection

Rethinking Object Detection in Retail Stores

YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design

Semantic MapNet: Building Allocentric Semantic Maps and Representations from Egocentric Views

Understanding Deformable Alignment in Video Super-Resolution

Deep Metric Learning with Graph Consistency

CNN Profiler on Polar Coordinate Images for Tropical Cyclone Structure Analysis

Commonsense Knowledge Aware Concept Selection For Diverse and Informative Visual Storytelling

Attention-based Multi-Level Fusion Network for Light Field Depth Estimation

Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty

Spatial-temporal Causal Inference for Partial Image-to-video Adaptation

Ref-NMS: Breaking Proposal Bottlenecks in Two-Stage Referring Expression Grounding

RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning

Dual Distribution Alignment Network for Generalizable Person Re-Identification

RGB-D Salient Object Detection via 3D Convolutional Neural Networks

Mind-the-Gap! Unsupervised Domain Adaptation for Text-Video Retrieval

Local Relation Learning for Face Forgery Detection

Deductive Learning for Weakly-Supervised 3D Human Pose Estimation via Uncalibrated Cameras

A Unified Multi-Scenario Attacking Network for Visual Object Tracking

SSD-GAN: Measuring the Realness in the Spatial and Spectral Domains

Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition

Cascade Network with Guided Loss and Hybrid Attention for Finding Good Correspondences

Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing

SSPC-Net: Semi-supervised Semantic 3D Point Cloud Segmentation Network

Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification

Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos

DramaQA: Character-Centered Video Story Understanding with Hierarchical QA

DeepCollaboration: Collaborative Generative and Discriminative Models for Class Incremental Learning

Split then Refine: Stacked Attention-guided ResUNets for Blind Single Image Visible Watermark Removal

RSGNet: Relation based Skeleton Graph Network for Crowded Scenes Pose Estimation

Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection

Arbitrary Video Style Transfer via Multi-Channel Correlation

Similarity Reasoning and Filtration for Image-Text Matching

Spatio-Temporal Difference Descriptor for Skeleton-Based Action Recognition

Towards Universal Physical Attacks on Single Object Tracking

Modeling the Probabilistic Distribution of Unlabeled Data for One-shot Medical Image Segmentation

Few-Shot Class-Incremental Learning via Relation Knowledge Distillation

MIEHDR CNN: Main Image Enhancement based Ghost-Free High Dynamic Range Imaging using Dual-Lens Systems

Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze

How to Save your Annotation Cost for Panoptic Segmentation?

DIRV: Dense Interaction Region Voting for End-to-End Human-Object Interaction Detection

DecAug: Augmenting HOI Detection via Decomposition

Partially Non-Autoregressive Image Captioning

Memory-Augmented Image Captioning

Edge-competing Pathological Liver Vessel Segmentation with Limited Labels

Visual Boundary Knowledge Translation for Foreground Segmentation

Learning Complex 3D Human Self-Contact

Rain Streak Removal via Dual Graph Convolutional Network

CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation

Deep Metric Learning with Self-Supervised Ranking

A Systematic Evaluation of Object Detection Networks for Scientific Plots

The Complexity of Object Association in Multiple Object Tracking

Learning Local Neighboring Structure for Robust 3D Shape Representation

Semantic-guided Reinforced Region Embedding for Generalized Zero-Shot Learning

Dynamic Graph Representation Learning for Video Dialog via Multi-Modal Shuffled Transformers

Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds

Analogical Image Translation for Fog Generation

Temporal ROI Align for Video Object Recognition

SMART Frame Selection for Action Recognition

Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning

Interpretable Graph Capsule Networks for Object Recognition

Class-Incremental Instance Segmentation via Multi-Teacher Networks

EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining

Order Regularization on Ordinal Loss for Head Pose, Age and Gaze Estimation

Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person Search

Spherical Image Generation from a Single Image by Considering Scene Symmetry

Progressive One-shot Human Parsing

Consistent-Separable Feature Representation for Semantic Segmentation

Error-Aware Density Isomorphism Reconstruction for Unsupervised Cross-Domain Crowd Counting

DropLoss for Long-Tail Instance Segmentation

Hand-Model-Aware Sign Language Recognition

Stratified Rule-Aware Network for Abstract Visual Reasoning

VIVO: Visual Vocabulary Pre-Training for Novel Object Captioning

Exploiting Relationship for Complex-scene Image Generation

Modeling Deep Learning Based Privacy Attacks on Physical Mail

PTN: A Poisson Transfer Network for Semi-supervised Few-shot Learning

Text-Guided Graph Neural Networks for Referring 3D Instance Segmentation

Initiative Defense against Facial Manipulation

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data

A Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization

Context-Aware Graph Convolution Network for Target Re-identification

Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network

Frequency Consistent Adaptation for Real World Super Resolution

Matching on Sets: Conquer Occluded Person Re-identification Without Alignment

GradingNet: Towards Providing Reliable Supervisions for Weakly Supervised Object Detection by Grading the Box Candidates

SSN3D: Self-Separated Network to Align Parts for 3D Convolution in Video Person Re-Identification

Training Binary Neural Network without Batch Normalization for Image Super-Resolution

What to Select: Pursuing Consistent Motion Segmentation from Multiple Geometric Models

Asynchronous Teacher Guided Bit-wise Hard Mining for Online Hashing

Deep Low-Contrast Image Enhancement using Structure Tensor Representation

Spectral Distribution Aware Image Generation

StarNet: towards Weakly Supervised Few-Shot Object Detection

Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation

Visual Comfort Aware-Reinforcement Learning for Depth Adjustment of Stereoscopic 3D Images

Dual Compositional Learning in Interactive Image Retrieval

End-to-End Differentiable Learning to HDR Image Synthesis for Multi-exposure Images

Structured Co-reference Graph Attention for Video-grounded Dialogue

AAAI Technical Track on Computer Vision II

Cross-Domain Grouping and Alignment for Domain Adaptive Semantic Segmentation

Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation

DASZL: Dynamic Action Signatures for Zero-shot Learning

Multi-level Distance Regularization for Deep Metric Learning

Dynamic to Static Lidar Scan Reconstruction Using Adversarially Trained Auto Encoder

Regularizing Attention Networks for Anomaly Detection in Visual Question Answering

Weakly-supervised Temporal Action Localization by Uncertainty Modeling

Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency

Patch-Wise Attention Network for Monocular Depth Estimation

Semi-Supervised Learning for Multi-Task Scene Understanding by Neural Graph Consensus

Static-Dynamic Interaction Networks for Offline Signature Verification

Proposal-Free Video Grounding with Contextual Pyramid Network

Write-a-speaker: Text-based Emotional and Rhythmic Talking-head Generation

Exploiting Learnable Joint Groups for Hand Pose Estimation

RTS3D: Real-time Stereo 3D Detection from 4D Feature-Consistency Embedding Space for Autonomous Driving

Adversarial Pose Regression Network for Pose-Invariant Face Recognitions

Category Dictionary Guided Unsupervised Domain Adaptation for Object Detection

Joint Semantic-geometric Learning for Polygonal Building Segmentation

Generalized Zero-Shot Learning via Disentangled Representation

Learning Omni-Frequency Region-adaptive Representations for Real Image Super-Resolution

Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation

Inference Fusion with Associative Semantics for Unseen Object Detection

Deep Unsupervised Image Hashing by Maximizing Bit Entropy

Sequential End-to-end Network for Efficient Person Search

SD-Pose: Semantic Decomposition for Cross-Domain 6D Object Pose Estimation

Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision

Query-Memory Re-Aggregation for Weakly-supervised Video Object Segmentation

Augmented Partial Mutual Learning with Frame Masking for Video Captioning

Exploiting Audio-Visual Consistency with Partial Supervision for Spatial Audio Generation

Single View Point Cloud Generation via Unified 3D Prototype

Self-Supervised Sketch-to-Image Synthesis

TIME: Text and Image Mutual-Translation Adversarial Networks

SA-BNN: State-Aware Binary Neural Network

Spatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation

F2Net: Learning to Focus on the Foreground for Unsupervised Video Object Segmentation

Toward Realistic Virtual Try-on Through Landmark Guided Shape Matching

Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling

FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion

Activity Image-to-Video Retrieval by Disentangling Appearance and Motion

Adaptive Pattern-Parameter Matching for Robust Pedestrian Detection

Temporal Segmentation of Fine-gained Semantic Action: A Motion-Centered Figure Skating Dataset

Learning Hybrid Relationships for Person Re-identification

Translate the Facial Regions You Like Using Self-Adaptive Region Translation

Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis

FontRL: Chinese Font Synthesis via Deep Reinforcement Learning

Hierarchical Information Passing Based Noise-Tolerant Hybrid Learning for Semi-Supervised Human Parsing

Delving into Variance Transmission and Normalization: Shift of Average Gradient Makes the Network Collapse

Aggregated Multi-GANs for Controlled 3D Human Motion Prediction

ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization

Weakly Supervised Temporal Action Localization Through Learning Explicit Subspaces for Action and Context

PointINet: Point Cloud Frame Interpolation Network

A Global Occlusion-Aware Approach to Self-Supervised Monocular Visual Odometry

PC-HMR: Pose Calibration for 3D Human Mesh Recovery from 2D Images/Videos

DeepDT: Learning Geometry From Delaunay Triangulation for Surface Reconstruction

Dual-level Collaborative Transformer for Image Captioning

HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation

SMIL: Multimodal Learning with Severely Missing Modality

Pyramidal Feature Shrinking for Salient Object Detection

Learning to Count via Unbalanced Optimal Transport

Scene Graph Embeddings Using Relative Similarity Supervision

Few-Shot Lifelong Learning

CARPe Posterum: A Convolutional Approach for Real-Time Pedestrian Path Prediction

Dynamic Anchor Learning for Arbitrary-Oriented Object Detection

Terrace-based Food Counting and Segmentation

Embodied Visual Active Learning for Semantic Segmentation

TDAF: Top-Down Attention Framework for Vision Tasks

Few-shot Font Generation with Localized Style Representations and Factorization

Learning Disentangled Representation for Fair Facial Attribute Classification via Fairness-aware Information Alignment

Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation

CHEF: Cross-modal Hierarchical Embeddings for Food Domain Retrieval

Explainable Models with Consistent Interpretations

Dual Adversarial Graph Neural Networks for Multi-label Cross-modal Retrieval

KGDet: Keypoint-Guided Fashion Detection

Learning Modulated Loss for Rotated Object Detection

MANGO: A Mask Attention Guided One-Stage Scene Text Spotter

REFINE: Prediction Fusion Network for Panoptic Segmentation

AutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks

DPFPS: Dynamic and Progressive Filter Pruning for Compressing Convolutional Neural Networks from Scratch

Efficient Certification of Spatial Robustness

Semantic Grouping Network for Video Captioning

Audio-Visual Localization by Synthetic Acoustic Image Generation

Enhanced Regularizers for Attributional Robustness

Progressive Network Grafting for Few-Shot Knowledge Distillation

Social-DPF: Socially Acceptable Distribution Prediction of Futures

Robust Knowledge Transfer via Hybrid Forward on the Teacher-Student Model

AttaNet: Attention-Augmented Network for Fast and Accurate Scene Parsing

To Choose or to Fuse? Scale Selection for Crowd Counting

Image Captioning with Context-Aware Auxiliary Guidance

Unsupervised Model Adaptation for Continual Semantic Segmentation

BSN++: Complementary Boundary Regressor with Scale-Balanced Relation Modeling for Temporal Action Proposal Generation

MangaGAN: Unpaired Photo-to-Manga Translation Based on The Methodology of Manga Drawing

MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection

Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging

Domain General Face Forgery Detection by Learning to Weight

Object-Centric Image Generation from Layouts

Structure-aware Person Image Generation with Pose Decomposition and Semantic Correlation

Gradient Regularized Contrastive Learning for Continual Domain Adaptation

Adversarial Training Reduces Information and Improves Transferability

Adversarial Turing Patterns from Cellular Automata

Artificial Dummies for Urban Dataset Augmentation

SCNet: Training Inference Sample Consistency for Instance Segmentation

Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning

AAAI Technical Track on Computer Vision III

Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding

Temporal Relational Modeling with Self-Supervision for Action Segmentation

Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution

Self-Domain Adaptation for Face Anti-Spoofing

Weakly Supervised Deep Hyperspherical Quantization for Image Retrieval

Camera-Aware Proxies for Unsupervised Person Re-Identification

Unsupervised 3D Learning for Shape Analysis via Multiresolution Instance Discrimination

PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network

Dynamic Position-aware Network for Fine-grained Image Recognition

Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection

Very Important Person Localization in Unconstrained Conditions: A New Benchmark

Teacher Guided Neural Architecture Search for Face Recognition

Deep Multi-Task Learning for Diabetic Retinopathy Grading in Fundus Images

Confidence-aware Non-repetitive Multimodal Transformers for TextCaps

Geodesic-HOF: 3D Reconstruction Without Cutting Corners

C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer

Semantic Consistency Networks for 3D Object Detection

Holistic Multi-View Building Analysis in the Wild with Projection Pooling

Stereopagnosia: Fooling Stereo Networks with Adversarial Perturbations

Generalising without Forgetting for Lifelong Person Re-Identification

Decentralised Learning from Independent Multi-Domain Labels for Person Re-Identification

Region-aware Global Context Modeling for Automatic Nerve Segmentation from Ultrasound Images

Precise Yet Efficient Semantic Calibration and Refinement in ConvNets for Real-time Polyp Segmentation from Colonoscopy Videos

Graph-to-Graph: Towards Accurate and Interpretable Online Handwritten Mathematical Expression Recognition

Learning Comprehensive Motion Representation for Action Recognition

MVFNet: Multi-View Fusion Network for Efficient Video Recognition

Anticipating Future Relations via Graph Growing for Action Prediction

Binaural Audio-Visual Localization

Beating Attackers At Their Own Games: Adversarial Example Detection Using Adversarial Gradient Directions

Shape-Pose Ambiguity in Learning 3D Reconstruction from Images

Boundary Proposal Network for Two-stage Natural Language Video Localization

Amodal Segmentation Based on Visible Region Segmentation and Shape Prior

Locate Globally, Segment Locally: A Progressive Architecture With Knowledge Review Network for Salient Object Detection

Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation

Imagine, Reason and Write: Visual Storytelling with Graph Knowledge and Relational Reasoning

Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation

Efficient Deep Image Denoising via Class Specific Convolution

Investigate Indistinguishable Points in Semantic Segmentation of 3D Point Cloud

Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud

Searching for Alignment in Face Recognition

GIF Thumbnails: Attract More Clicks to Your Videos

FaceController: Controllable Attribute Editing for Face in the Wild

AnchorFace: An Anchor-based Facial Landmark Detector Across Large Poses

Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion

Learning Semantic Context from Normal Samples for Unsupervised Anomaly Detection

Non-Autoregressive Coarse-to-Fine Video Captioning

Learning to Attack Real-World Models for Person Re-identification via Virtual-Guided Meta-Learning

Object Relation Attention for Image Paragraph Captioning

Adversarial Robustness through Disentangled Representations

CPCGAN: A Controllable 3D Point Cloud Generative Adversarial Network with Semantic Label Generating

R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

One-shot Face Reenactment Using Appearance Adaptive Normalization

A Case Study of the Shortcut Effects in Visual Commonsense Reasoning

Instance Mining with Class Feature Banks for Weakly Supervised Object Detection

Multimodal Fusion via Teacher-Student Network for Indoor Action Recognition

ERNIE-ViL: Knowledge Enhanced Vision-Language Representations through Scene Graphs

High-Resolution Deep Image Matting

CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks

Structure-Consistent Weakly Supervised Salient Object Detection with Local Saliency Coherence

Fast and Compact Bilinear Pooling by Shifted Random Maclaurin

Simple and Effective Stochastic Neural Networks

Learning Visual Context for Group Activity Recognition

StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke Encoding

Demodalizing Face Recognition with Synthetic Samples

EMLight: Lighting Estimation via Spherical Distribution Approximation

Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards a Fourier Perspective

SPIN: Structure-Preserving Inner Offset Network for Scene Text Recognition

Visual Tracking via Hierarchical Deep Reinforcement Learning

One for More: Selecting Generalizable Samples for Generalizable ReID Model

Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation

SIMPLE: SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation

Enhancing Audio-Visual Association with Self-Supervised Curriculum Learning

Unsupervised Domain Adaptation for Person Re-identification via Heterogeneous Graph Alignment

Proactive Privacy-preserving Learning for Retrieval

A Novel Visual Interpretability for Deep Neural Networks by Optimizing Activation Maps with Perturbation

Point Cloud Semantic Scene Completion from RGB-D Images

Consensus Graph Representation Learning for Better Grounded Image Captioning

BoW Pooling: A Plug-and-Play Unit for Feature Aggregation of Point Clouds

Diverse Knowledge Distillation for End-to-End Person Search

Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud

PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection

Efficient License Plate Recognition via Holistic Position Attention

Bag of Tricks for Long-Tailed Visual Recognition with Deep Convolutional Neural Networks

Depth Privileged Object Detection in Indoor Scenes via Deformation Hallucination

Learning Flexibly Distributional Representation for Low-quality 3D Face Recognition

IA-GM: A Deep Bidirectional Learning Method for Graph Matching

Distribution Adaptive INT8 Quantization for Training CNNs

Context-Guided Adaptive Network for Efficient Human Pose Estimation

ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation

Robust Lightweight Facial Expression Recognition Network with Label Distribution Training

Joint Color-irrelevant Consistency Learning and Identity-aware Modality Adaptation for Visible-infrared Cross Modality Person Re-identification

Robust Multi-Modality Person Re-identification

Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification

RESA: Recurrent Feature-Shift Aggregator for Lane Detection

CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud

Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture Recognition

Deep Semantic Dictionary Learning for Multi-label Image Classification

Model Uncertainty Guides Visual Object Tracking

Optimizing Information Theory Based Bitwise Bottlenecks for Efficient Mixed-Precision Activation Quantization

Inferring Camouflaged Objects by Texture-Aware Interactive Guidance Network

Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps

Fooling Thermal Infrared Pedestrian Detectors in Real World Using Small Bulbs

ASHF-Net: Adaptive Sampling and Hierarchical Folding Network for Robust Point Cloud Completion

AAAI Technical Track on Constraint Satisfaction and Optimization

New Length Dependent Algorithm for Maximum Satisfiability Problem

Online Search with Maximum Clearance

Counting Maximal Satisfiable Subsets

Learning To Scale Mixed-Integer Programs

A SAT-based Resolution of Lam's Problem

Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization

Necessary and Sufficient Conditions for Avoiding Reopenings in Best First Suboptimal Search with General Bounding Functions

A Sharp Leap from Quantified Boolean Formula to Stochastic Boolean Satisfiability Solving

An Improved Upper Bound for SAT

Solving Infinite-Domain CSPs Using the Patchwork Property

Disjunctive Temporal Problems under Structural Restrictions

Optimal Decision Trees for Nonlinear Metrics

Teaching the Old Dog New Tricks: Supervised Learning with Constraints

Cutting to the Core of Pseudo-Boolean Optimization: Combining Core-Guided Search with Cutting Planes Reasoning

Optimising Automatic Calibration of Electric Muscle Stimulation

Certifying Parity Reasoning Efficiently Using Pseudo-Boolean Proofs

Finding Diverse Trees, Paths, and More

Scalable Verification of Quantized Neural Networks

Integrated Optimization of Bipartite Matching and Its Stochastic Behavior: New Formulation and Approximation Algorithm via Min-cost Flow Optimization

A Scalable Two Stage Approach to Computing Optimal Decision Sets

Smooth Convex Optimization Using Sub-Zeroth-Order Oracles

Binary Matrix Factorisation via Column Generation

Backdoor Decomposable Monotone Circuits and Propagation Complete Encodings

On Continuous Local BDD-Based Search for Hybrid SAT Solving

The Power of Literal Equivalence in Model Counting

Parallel Constraint Acquisition

Towards More Practical and Efficient Automatic Dominance Breaking

Dependency Stochastic Boolean Satisfiability: A Logical Formalism for NEXPTIME Decision Problems with Uncertainty

Satisfiability and Algorithms for Non-uniform Random k-SAT

Turbocharging Treewidth-Bounded Bayesian Network Structure Learning

SAT-based Decision Tree Learning for Large Data Sets

LCollision: Fast Generation of Collision-Free Human Poses using Learned Non-Penetration Constraints

Symmetric Component Caching for Model Counting on Combinatorial Instances

Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies

AAAI Technical Track on Data Mining and Knowledge Management

Extreme k-Center Clustering

Beyond Low-frequency Information in Graph Convolutional Networks

Graph Heterogeneous Multi-Relational Recommendation

Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure

Revisiting Consistent Hashing with Bounded Loads

A User-Adaptive Layer Selection Framework for Very Deep Sequential Recommender Models

Leveraging Table Content for Zero-shot Text-to-SQL with Meta-Learning

Towards Faster Deep Collaborative Filtering via Hierarchical Decision Networks

Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems

PASSLEAF: A Pool-bAsed Semi-Supervised LEArning Framework for Uncertain Knowledge Graph Embedding

Graph Neural Network-Based Anomaly Detection in Multivariate Time Series

A Hybrid Bandit Framework for Diversified Recommendation

Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries

Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs

Exploiting Behavioral Consistence for Universal User Representation

NeuralAC: Learning Cooperation and Competition Effects for Match Outcome Prediction

Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks

GAN Ensemble for Anomaly Detection

Complete Closed Time Intervals-Related Patterns Mining

Online Learning in Variable Feature Spaces under Incomplete Supervision

Knowledge-aware Coupled Graph Neural Network for Social Recommendation

Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation

Anomaly Attribution with Likelihood Compensation

LREN: Low-Rank Embedded Network for Sample-Free Hyperspectral Anomaly Detection

On Estimating Recommendation Evaluation Metrics under Sampling

Randomized Generation of Adversary-aware Fake Knowledge Graphs to Combat Intellectual Property Theft

PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation

Disposable Linear Bandits for Online Recommendations

Hierarchical Negative Binomial Factorization for Recommender Systems on Implicit Feedback

Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting

Rejection Sampling for Weighted Jaccard Similarity Revisited

GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks

Cross-Oilfield Reservoir Classification via Multi-Scale Sensor Knowledge Transfer

FedRec++: Lossless Federated Recommendation with Explicit Feedback

HMS: A Hierarchical Solver with Dependency-Enhanced Understanding for Math Word Problem

Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction

Noninvasive Self-attention for Side Information Fusion in Sequential Recommendation

Visual Pivoting for (Unsupervised) Entity Alignment

Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph

Learning to Pre-train Graph Neural Networks

Knowledge-Enhanced Top-K Recommendation in Poincar茅 Ball

Communicative Message Passing for Inductive Relation Reasoning

Learning Accurate and Interpretable Decision Rule Sets from Neural Networks

Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning

U-BERT: Pre-training User Representations for Improved Recommendation

DocParser: Hierarchical Document Structure Parsing from Renderings

Knowledge-Driven Distractor Generation for Cloze-Style Multiple Choice Questions

Group Testing on a Network

Detecting Beneficial Feature Interactions for Recommender Systems

A Hybrid Probabilistic Approach for Table Understanding

Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs

Dynamic Memory based Attention Network for Sequential Recommendation

GaussianPath:A Bayesian Multi-Hop Reasoning Framework for Knowledge Graph Reasoning

GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting

Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective

Coupling Macro-Sector-Micro Financial Indicators for Learning Stock Representations with Less Uncertainty

Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation

Learning to Recommend from Sparse Data via Generative User Feedback

How Do We Move: Modeling Human Movement with System Dynamics

Learning to Truncate Ranked Lists for Information Retrieval

Fairness-aware News Recommendation with Decomposed Adversarial Learning

Hybrid-order Stochastic Block Model

Inductive Graph Neural Networks for Spatiotemporal Kriging

Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation

AttnMove: History Enhanced Trajectory Recovery via Attentional Network

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation

A General Offline Reinforcement Learning Framework for Interactive Recommendation

Hierarchical Reinforcement Learning for Integrated Recommendation

Out-of-Town Recommendation with Travel Intention Modeling

Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field

Transformer-Style Relational Reasoning with Dynamic Memory Updating for Temporal Network Modeling

A Unified Pretraining Framework for Passage Ranking and Expansion

Dynamic Knowledge Graph Alignment

Rethinking Graph Regularization for Graph Neural Networks

Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling

Why Do Attributes Propagate in Graph Convolutional Neural Networks?

Relaxed Clustered Hawkes Process for Student Procrastination Modeling in MOOCs

Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks

Coupled Layer-wise Graph Convolution for Transportation Demand Prediction

Deep Graph-neighbor Coherence Preserving Network for Unsupervised Cross-modal Hashing

Dual Sparse Attention Network For Session-based Recommendation

Self-Supervised Prototype Representation Learning for Event-Based Corporate Profiling

AugSplicing: Synchronized Behavior Detection in Streaming Tensors

Taxonomy Completion via Triplet Matching Network

Tripartite Collaborative Filtering with Observability and Selection for Debiasing Rating Estimation on Missing-Not-at-Random Data

Generalized Relation Learning with Semantic Correlation Awareness for Link Prediction

A Graph-based Relevance Matching Model for Ad-hoc Retrieval

Heterogeneous Graph Structure Learning for Graph Neural Networks

Cold-start Sequential Recommendation via Meta Learner

Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay

Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction

Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks

Adversarial Directed Graph Embedding

Relation-Aware Neighborhood Matching Model for Entity Alignment

AAAI Technical Track Focus Area on AI for Conference Organization and Delivery

Argument Mining Driven Analysis of Peer-Reviews

Uncovering Latent Biases in Text: Method and Application to Peer Review

A Market-Inspired Bidding Scheme for Peer Review Paper Assignment

A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences

Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment

AAAI Technical Track Focus Area on AI Responses to the COVID-19 Pandemic

Savable but Lost Lives when ICU Is Overloaded: a Model from 733 Patients in Epicenter Wuhan, China

Persistence of Anti-vaccine Sentiment in Social Networks Through Strategic Interactions

Automated Model Design and Benchmarking of Deep Learning Models for COVID-19 Detection with Chest CT Scans

STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization

Transfer Graph Neural Networks for Pandemic Forecasting

MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation

Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19

Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks

Context Matters: Graph-based Self-supervised Representation Learning for Medical Images

Tracking Disease Outbreaks from Sparse Data with Bayesian Inference

C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak

AAAI Technical Track Focus Area on Neuro-Symbolic AI

Conversational Neuro-Symbolic Commonsense Reasoning

Interpretable Actions: Controlling Experts with Understandable Commands

Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering

Aligning Artificial Neural Networks and Ontologies towards Explainable AI

Planning from Pixels in Atari with Learned Symbolic Representations

Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers

Learning by Fixing: Solving Math Word Problems with Weak Supervision

Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders

Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic

Explaining Neural Matrix Factorization with Gradient Rollback

A Scalable Reasoning and Learning Approach for Neural-Symbolic Stream Fusion

Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units

A Unified Framework for Planning with Learned Neural Network Transition Models

Classification by Attention: Scene Graph Classification with Prior Knowledge

Differentiable Inductive Logic Programming for Structured Examples

Encoding Human Domain Knowledge to Warm Start Reinforcement Learning

Neural-Symbolic Integration: A Compositional Perspective

Adaptive Teaching of Temporal Logic Formulas to Preference-based Learners

AAAI Technical Track on Game Theory and Economic Paradigms

Double Oracle Algorithm for Computing Equilibria in Continuous Games

A Few Queries Go a Long Way: Information-Distortion Tradeoffs in Matching

Representative Proxy Voting

Forming Better Stable Solutions in Group Formation Games Inspired by Internet Exchange Points (IXPs)

Achieving Envy-freeness and Equitability with Monetary Transfers

Proportionally Representative Participatory Budgeting with Ordinal Preferences

Fair and Truthful Mechanisms for Dichotomous Valuations

Bayesian Persuasion under Ex Ante and Ex Post Constraints

Defending against Contagious Attacks on a Network with Resource Reallocation

Achieving Proportionality up to the Maximin Item with Indivisible Goods

The Price of Connectivity in Fair Division

Dividing a Graphical Cake

Maximin Fairness with Mixed Divisible and Indivisible Goods

Protecting the Protected Group: Circumventing Harmful Fairness

Selfish Creation of Social Networks

On the Complexity of Finding Justifications for Collective Decisions

Preserving Condorcet Winners under Strategic Manipulation

Reaching Individually Stable Coalition Structures in Hedonic Games

Reinforcement Learning of Sequential Price Mechanisms

Margin of Victory in Tournaments: Structural and Experimental Results

Welfare Guarantees in Schelling Segregation

Persuading Voters in District-based Elections

Signaling in Bayesian Network Congestion Games: the Subtle Power of Symmetry

Computing Quantal Stackelberg Equilibrium in Extensive-Form Games

Fair and Efficient Allocations under Subadditive Valuations

Scalable Equilibrium Computation in Multi-agent Influence Games on Networks

Proportional Representation under Single-Crossing Preferences Revisited

Computational Analyses of the Electoral College: Campaigning Is Hard But Approximately Manageable

Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation

On Fair Division under Heterogeneous Matroid Constraints

PoA of Simple Auctions with Interdependent Values

Mind the Gap: Cake Cutting With Separation

United for Change: Deliberative Coalition Formation to Change the Status Quo

Incentivizing Truthfulness Through Audits in Strategic Classification

Almost Envy-freeness, Envy-rank, and Nash Social Welfare Matchings

Faster Game Solving via Predictive Blackwell Approachability: Connecting Regret Matching and Mirror Descent

Bandit Linear Optimization for Sequential Decision Making and Extensive-Form Games

Model-Free Online Learning in Unknown Sequential Decision Making Problems and Games

Simultaneous 2nd Price Item Auctions with No-Underbidding

Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions

Condorcet Relaxation In Spatial Voting

Present-Biased Optimization

Efficient Truthful Scheduling and Resource Allocation through Monitoring

Infinite-Dimensional Fisher Markets: Equilibrium, Duality and Optimization

Fair and Efficient Online Allocations with Normalized Valuations

An Analysis of Approval-Based Committee Rules for 2D-Euclidean Elections

Aggregating Binary Judgments Ranked by Accuracy

District-Fair Participatory Budgeting

Fair and Efficient Allocations under Lexicographic Preferences

Necessarily Optimal One-Sided Matchings

Computing the Proportional Veto Core

Multi-Scale Games: Representing and Solving Games on Networks with Group Structure

Multi-Party Campaigning

Classification with Strategically Withheld Data

On the PTAS for Maximin Shares in an Indivisible Mixed Manna

Evolution Strategies for Approximate Solution of Bayesian Games

Safe Search for Stackelberg Equilibria in Extensive-Form Games

Budget Feasible Mechanisms Over Graphs

On the Approximation of Nash Equilibria in Sparse Win-Lose Multi-player Games

Trembling-Hand Perfection and Correlation in Sequential Games

Complexity and Algorithms for Exploiting Quantal Opponents in Large Two-Player Games

Hindsight and Sequential Rationality of Correlated Play

On Fair and Efficient Allocations of Indivisible Goods

Coalition Formation in Multi-defender Security Games

Majority Opinion Diffusion in Social Networks: An Adversarial Approach

Fair and Efficient Allocations with Limited Demands

Scarce Societal Resource Allocation and the Price of (Local) Justice

From Behavioral Theories to Econometrics: Inferring Preferences of Human Agents from Data on Repeated Interactions

Preference Elicitation as Average-Case Sorting

Market-Based Explanations of Collective Decisions

A Permutation-Equivariant Neural Network Architecture For Auction Design

Estimating 伪-Rank by Maximizing Information Gain

Online Posted Pricing with Unknown Time-Discounted Valuations

The Maximin Support Method: An Extension of the D鈥橦ondt Method to Approval-Based Multiwinner Elections

Solution Concepts in Hierarchical Games Under Bounded Rationality With Applications to Autonomous Driving

Modeling Voters in Multi-Winner Approval Voting

Coupon Design in Advertising Systems

Restricted Domains of Dichotomous Preferences with Possibly Incomplete Information

Facility鈥檚 Perspective to Fair Facility Location Problems

The Smoothed Complexity of Computing Kemeny and Slater Rankings

If You Like Shapley Then You鈥檒l Love the Core

A Model of Winners Allocation

Targeted Negative Campaigning: Complexity and Approximations

Finding and Certifying (Near-)Optimal Strategies in Black-Box Extensive-Form Games

Automated Mechanism Design for Classification with Partial Verification

Incentive-Aware PAC Learning

Classification with Few Tests through Self-Selection

Computing Ex Ante Coordinated Team-Maxmin Equilibria in Zero-Sum Multiplayer Extensive-Form Games

Power in Liquid Democracy

AAAI Technical Track on Human-Computation and Crowd Sourcing

Learning from Crowds by Modeling Common Confusions

Time to Transfer: Predicting and Evaluating Machine-Human Chatting Handoff

Teaching Active Human Learners

AAAI Technical Track on Humans and AI

Automated Storytelling via Causal, Commonsense Plot Ordering

MARTA: Leveraging Human Rationales for Explainable Text Classification

Human Uncertainty Inference via Deterministic Ensemble Neural Networks

Learning to Sit: Synthesizing Human-Chair Interactions via Hierarchical Control

User Driven Model Adjustment via Boolean Rule Explanations

Classification Under Human Assistance

Wasserstein Distributionally Robust Inverse Multiobjective Optimization

Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Network

ActionBert: Leveraging User Actions for Semantic Understanding of User Interfaces

Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle

Contrastive Adversarial Learning for Person Independent Facial Emotion Recognition

AI-Assisted Scientific Data Collection with Iterative Human Feedback

Improving the Performance-Compatibility Tradeoff with Personalized Objective Functions

Indecision Modeling

Narrative Plan Generation with Self-Supervised Learning

Uncertain Graph Neural Networks for Facial Action Unit Detection

Learning Rewards From Linguistic Feedback

Bounded Risk-Sensitive Markov Games: Forward Policy Design and Inverse Reward Learning with Iterative Reasoning and Cumulative Prospect Theory

Content Learning with Structure-Aware Writing: A Graph-Infused Dual Conditional Variational Autoencoder for Automatic Storytelling

A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation

Inferring Emotion from Large-scale Internet Voice Data: A Semi-supervised Curriculum Augmentation based Deep Learning Approach

AAAI Technical Track on Intelligent Robots

Automatic Generation of Flexible Plans via Diverse Temporal Planning

BT Expansion: a Sound and Complete Algorithm for Behavior Planning of Intelligent Robots with Behavior Trees

I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting

Enabling Fast Instruction-Based Modification of Learned Robot Skills

Consistent Right-Invariant Fixed-Lag Smoother with Application to Visual Inertial SLAM

Supervised Training of Dense Object Nets using Optimal Descriptors for Industrial Robotic Applications

DenserNet: Weakly Supervised Visual Localization Using Multi-Scale Feature Aggregation

Learning Intuitive Physics with Multimodal Generative Models

SCAN: A Spatial Context Attentive Network for Joint Multi-Agent Intent Prediction

IDOL: Inertial Deep Orientation-Estimation and Localization

Differentiable Fluids with Solid Coupling for Learning and Control

CMAX++ : Leveraging Experience in Planning and Execution using Inaccurate Models

Generative Partial Visual-Tactile Fused Object Clustering

VMLoc: Variational Fusion For Learning-Based Multimodal Camera Localization

AAAI Technical Track on Knowledge Representation and Reasoning

Argumentation Frameworks with Strong and Weak Constraints: Semantics and Complexity

A General Setting for Gradual Semantics Dealing with Similarity

Living Without Beth and Craig: Definitions and Interpolants in Description Logics with Nominals and Role Inclusions

Equivalent Causal Models

The Counterfactual NESS Definition of Causation

Network Satisfaction for Symmetric Relation Algebras with a Flexible Atom

Conditional Inference under Disjunctive Rationality

Algebra of Modular Systems: Containment and Equivalence

Certifying Top-Down Decision-DNNF Compilers

Contextual Conditional Reasoning

Preferred Explanations for Ontology-Mediated Queries under Existential Rules

Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs

A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving

Recursion in Abstract Argumentation is Hard --- On the Complexity of Semantics Based on Weak Admissibility

The Complexity Landscape of Claim-Augmented Argumentation Frameworks

On the Complexity of Sum-of-Products Problems over Semirings

Treewidth-Aware Complexity in ASP: Not all Positive Cycles are Equally Hard

SMT-based Safety Checking of Parameterized Multi-Agent Systems

A Simple Framework for Cognitive Planning

Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics

Knowledge-Base Degrees of Inconsistency: Complexity and Counting

Constraint Logic Programming for Real-World Test Laboratory Scheduling

Mining EL Bases with Adaptable Role Depth

REM-Net: Recursive Erasure Memory Network for Commonsense Evidence Refinement

(Comet-) Atomic 2020: On Symbolic and Neural Commonsense Knowledge Graphs

Commonsense Knowledge Augmentation for Low-Resource Languages via Adversarial Learning

Parameterized Logical Theories

Learning Term Embeddings for Lexical Taxonomies

KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning

Parameterized Complexity of Logic-Based Argumentation in Schaefer's Framework

Ranking Sets of Defeasible Elements in Preferential Approaches to Structured Argumentation: Postulates, Relations, and Characterizations

GENSYNTH: Synthesizing Datalog Programs without Language Bias

Parameterized Complexity of Small Decision Tree Learning

Interpreting Neural Networks as Quantitative Argumentation Frameworks

ChronoR: Rotation Based Temporal Knowledge Graph Embedding

Quantification of Resource Production Incompleteness

Stratified Negation in Datalog with Metric Temporal Operators

Strong Explanations in Abstract Argumentation

On the Tractability of SHAP Explanations

On Exploiting Hitting Sets for Model Reconciliation

Focused Inference and System P

On-the-fly Synthesis for LTL over Finite Traces

Testing Independence Between Linear Combinations for Causal Discovery

AAAI Technical Track on Machine Learning I

SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors

DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits

Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration

Semi-supervised Sequence Classification through Change Point Detection

Learning Invariant Representations using Inverse Contrastive Loss

Learned Bi-Resolution Image Coding using Generalized Octave Convolutions

Deep Bayesian Quadrature Policy Optimization

eTREE: Learning Tree-structured Embeddings

Does Explainable Artificial Intelligence Improve Human Decision-Making?

Decentralized Multi-Agent Linear Bandits with Safety Constraints

Computing an Efficient Exploration Basis for Learning with Univariate Polynomial Features

Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning

An Enhanced Advising Model in Teacher-Student Framework using State Categorization

On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory

The Tractability of SHAP-Score-Based Explanations for Classification over Deterministic and Decomposable Boolean Circuits

TabNet: Attentive Interpretable Tabular Learning

Robust Model Compression Using Deep Hypotheses

Deep Radial-Basis Value Functions for Continuous Control

DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation

Correlative Channel-Aware Fusion for Multi-View Time Series Classification

Deterministic Mini-batch Sequencing for Training Deep Neural Networks

Relative Variational Intrinsic Control

A Theory of Independent Mechanisms for Extrapolation in Generative Models

ExGAN: Adversarial Generation of Extreme Samples

Ordinal Historical Dependence in Graphical Event Models with Tree Representations

Characterizing the Loss Landscape in Non-Negative Matrix Factorization

Understanding Decoupled and Early Weight Decay

Communication-Aware Collaborative Learning

Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks

Fast Training of Provably Robust Neural Networks by SingleProp

Sample-Specific Output Constraints for Neural Networks

Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints

Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness

Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently

Exploiting Diverse Characteristics and Adversarial Ambivalence for Domain Adaptive Segmentation

Time Series Domain Adaptation via Sparse Associative Structure Alignment

A Blind Block Term Decomposition of High Order Tensors

Open-Set Recognition with Gaussian Mixture Variational Autoencoders

Provably Secure Federated Learning against Malicious Clients

Dual Quaternion Knowledge Graph Embeddings

Counterfactual Explanations for Oblique Decision Trees:Exact, Efficient Algorithms

Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning

Frivolous Units: Wider Networks Are Not Really That Wide

Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift Algorithm

High-Confidence Off-Policy (or Counterfactual) Variance Estimation

A Multi-step-ahead Markov Conditional Forward Model with Cube Perturbations for Extreme Weather Forecasting

Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications

On Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems

Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks

Differentially Private Decomposable Submodular Maximization

Using Hindsight to Anchor Past Knowledge in Continual Learning

Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models

Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Learning

Addressing Action Oscillations through Learning Policy Inertia

Cross-Layer Distillation with Semantic Calibration

Distributed Ranking with Communications: Approximation Analysis and Applications

THOR, Trace-based Hardware-driven Layer-Oriented Natural Gradient Descent Computation

Neural Relational Inference with Efficient Message Passing Mechanisms

Fitting the Search Space of Weight-sharing NAS with Graph Convolutional Networks

Deep Spiking Neural Network with Neural Oscillation and Spike-Phase Information

HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks

NASGEM: Neural Architecture Search via Graph Embedding Method

Neighborhood Consensus Networks for Unsupervised Multi-view Outlier Detection

Self-Progressing Robust Training

Continuous-Time Attention for Sequential Learning

Transfer Learning for Efficient Iterative Safety Validation

Computationally Tractable Riemannian Manifolds for Graph Embeddings

Cost-aware Graph Generation: A Deep Bayesian Optimization Approach

Type-augmented Relation Prediction in Knowledge Graphs

The Value-Improvement Path: Towards Better Representations for Reinforcement Learning

Loop Estimator for Discounted Values in Markov Reward Processes

Differentially Private Stochastic Coordinate Descent

Generalized Adversarially Learned Inference

Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models

Learning with Retrospection

Mercer Features for Efficient Combinatorial Bayesian Optimization

Differentially Private and Communication Efficient Collaborative Learning

Knowledge Refinery: Learning from Decoupled Label

Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization

Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences

A One-Size-Fits-All Solution to Conservative Bandit Problems

Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback

Knowledge Refactoring for Inductive Program Synthesis

Semi-Supervised Metric Learning: A Deep Resurrection

Reinforcement Learning with Trajectory Feedback

The Parameterized Complexity of Clustering Incomplete Data

Learning Prediction Intervals for Model Performance

Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities

Projection-Free Bandit Optimization with Privacy Guarantees

Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems

Regret Bounds for Batched Bandits

Almost Linear Time Density Level Set Estimation via DBSCAN

Deep Graph Spectral Evolution Networks for Graph Topological Evolution

Adversarial Training and Provable Robustness: A Tale of Two Objectives

Learning a Gradient-free Riemannian Optimizer on Tangent Spaces

Learning to Reweight with Deep Interactions

Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting

UAG: Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks

SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

Learning to Augment for Data-scarce Domain BERT Knowledge Distillation

Collaborative Group Learning

Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression

Few-Shot One-Class Classification via Meta-Learning

Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning

Agreement-Discrepancy-Selection: Active Learning with Progressive Distribution Alignment

Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances

AAAI Technical Track on Machine Learning II

HiGAN: Handwriting Imitation Conditioned on Arbitrary-Length Texts and Disentangled Styles

Diffusion Network Inference from Partial Observations

Stabilizing Q Learning Via Soft Mellowmax Operator

On the Convergence of Communication-Efficient Local SGD for Federated Learning

A Trace-restricted Kronecker-Factored Approximation to Natural Gradient

Addressing Domain Gap via Content Invariant Representation for Semantic Segmentation

Increasing Iterate Averaging for Solving Saddle-Point Problems

Uncertainty-Aware Multi-View Representation Learning

Justicia: A Stochastic SAT Approach to Formally Verify Fairness

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations

Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization

Attentive Neural Point Processes for Event Forecasting

Revisiting Iterative Back-Translation from the Perspective of Compositional Generalization

Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation

Towards Reusable Network Components by Learning Compatible Representations

High-Dimensional Bayesian Optimization via Tree-Structured Additive Models

Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability

DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning

Liquid Time-constant Networks

Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs

Analysing the Noise Model Error for Realistic Noisy Label Data

Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size

Scaling-Up Robust Gradient Descent Techniques

Learning Model-Based Privacy Protection under Budget Constraints

Graph Game Embedding

Topology Distance: A Topology-Based Approach for Evaluating Generative Adversarial Networks

Storage Fit Learning with Feature Evolvable Streams

Reinforcement Learning Based Multi-Agent Resilient Control: From Deep Neural Networks to an Adaptive Law

Slimmable Generative Adversarial Networks

Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond

Gaussian Process Priors for View-Aware Inference

Boosting Multi-task Learning Through Combination of Task Labels - with Applications in ECG Phenotyping

OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization

Multi-scale Graph Fusion for Co-saliency Detection

Continual Learning by Using Information of Each Class Holistically

Predictive Adversarial Learning from Positive and Unlabeled Data

Multidimensional Uncertainty-Aware Evidential Neural Networks

Adversarial Defence by Diversified Simultaneous Training of Deep Ensembles

Accelerating Continuous Normalizing Flow with Trajectory Polynomial Regularization

Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition

Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning

ACMo: Angle-Calibrated Moment Methods for Stochastic Optimization

Personalized Cross-Silo Federated Learning on Non-IID Data

Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits

Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling

Accurate and Robust Feature Importance Estimation under Distribution Shifts

Variance Penalized On-Policy and Off-Policy Actor-Critic

Constructing a Fair Classifier with Generated Fair Data

Neural Utility Functions

IB-GAN: Disentangled Representation Learning with Information Bottleneck Generative Adversarial Networks

Active Bayesian Assessment of Black-Box Classifiers

Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching

Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications

Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks

Clustering Ensemble Meets Low-rank Tensor Approximation

Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks

LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification

Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks

Power up! Robust Graph Convolutional Network via Graph Powering

Balanced Open Set Domain Adaptation via Centroid Alignment

Linearly Replaceable Filters for Deep Network Channel Pruning

A Sample-Efficient Algorithm for Episodic Finite-Horizon MDP with Constraints

Winning Lottery Tickets in Deep Generative Models

Exploration via State influence Modeling

Deep Probabilistic Canonical Correlation Analysis

Learning Generalized Relational Heuristic Networks for Model-Agnostic Planning

A Recipe for Global Convergence Guarantee in Deep Neural Networks

Bayesian Dynamic Mode Decomposition with Variational Matrix Factorization

Improving Fairness and Privacy in Selection Problems

A Flexible Framework for Communication-Efficient Machine Learning

GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning

Understanding Catastrophic Overfitting in Single-step Adversarial Training

Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder

Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network

DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation

Kernel-convoluted Deep Neural Networks with Data Augmentation

Neural Sequence-to-grid Module for Learning Symbolic Rules

Visual Concept Reasoning Networks

Sparsity Aware Normalization for GANs

HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference

Nearly Linear-Time, Parallelizable Algorithms for Non-Monotone Submodular Maximization

Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees

Positions, Channels, and Layers: Fully Generalized Non-Local Network for Singer Identification

MolGrow: A Graph Normalizing Flow for Hierarchical Molecular Generation

Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters

Hypothesis Disparity Regularized Mutual Information Maximization

Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables

Metrics and Continuity in Reinforcement Learning

Lipschitz Lifelong Reinforcement Learning

Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks

Learnable Dynamic Temporal Pooling for Time Series Classification

Interpretable Embedding Procedure Knowledge Transfer via Stacked Principal Component Analysis and Graph Neural Network

Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer

Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients

Enhancing Parameter-Free Frank Wolfe with an Extra Subproblem

Unsupervised Active Learning via Subspace Learning

LRSC: Learning Representations for Subspace Clustering

GoT: a Growing Tree Model for Clustering Ensemble

VSQL: Variational Shadow Quantum Learning for Classification

High Fidelity GAN Inversion via Prior Multi-Subspace Feature Composition

ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification

A Bayesian Approach for Subset Selection in Contextual Bandits

Self-Paced Two-dimensional PCA

Learning Intact Features by Erasing-Inpainting for Few-shot Classification

Token-Aware Virtual Adversarial Training in Natural Language Understanding

AAAI Technical Track on Machine Learning III

Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

Bayesian Distributional Policy Gradients

Learning Graph Neural Networks with Approximate Gradient Descent

Multi-View Representation Learning with Manifold Smoothness

Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation

Sublinear Classical and Quantum Algorithms for General Matrix Games

A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data

Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints

MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements

Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding

One-shot Graph Neural Architecture Search with Dynamic Search Space

Scheduled Sampling in Vision-Language Pretraining with Decoupled Encoder-Decoder Network

Online Optimal Control with Affine Constraints

TRQ: Ternary Neural Networks With Residual Quantization

Contrastive Clustering

Longitudinal Deep Kernel Gaussian Process Regression

Large Norms of CNN Layers Do Not Hurt Adversarial Robustness

Doubly Residual Neural Decoder: Towards Low-Complexity High-Performance Channel Decoding

From Label Smoothing to Label Relaxation

Sample Selection for Universal Domain Adaptation

Class-Attentive Diffusion Network for Semi-Supervised Classification

Auto-Encoding Transformations in Reparameterized Lie Groups for Unsupervised Learning

Multi-Proxy Wasserstein Classifier for Image Classification

TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning

Learning a Few-shot Embedding Model with Contrastive Learning

Unchain the Search Space with Hierarchical Differentiable Architecture Search

Overcoming Catastrophic Forgetting in Graph Neural Networks

Stable Adversarial Learning under Distributional Shifts

Hierarchical Multiple Kernel Clustering

Dynamically Grown Generative Adversarial Networks

FLAME: Differentially Private Federated Learning in the Shuffle Model

Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision

Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning

ROSITA: Refined BERT cOmpreSsion with InTegrAted techniques

Task Aligned Generative Meta-learning for Zero-shot Learning

Learning from eXtreme Bandit Feedback

Improving Causal Discovery By Optimal Bayesian Network Learning

Stochastic Graphical Bandits with Adversarial Corruptions

Stochastic Bandits with Graph Feedback in Non-Stationary Environments

Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning

Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors

PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector

Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices

Semi-supervised Medical Image Segmentation through Dual-task Consistency

Adaptive Knowledge Driven Regularization for Deep Neural Networks

Multi-Domain Multi-Task Rehearsal for Lifelong Learning

On the Adequacy of Untuned Warmup for Adaptive Optimization

Learning Representations for Incomplete Time Series Clustering

Joint-Label Learning by Dual Augmentation for Time Series Classification

Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport

Sequential Attacks on Kalman Filter-based Forward Collision Warning Systems

Exact Reduction of Huge Action Spaces in General Reinforcement Learning

Composite Adversarial Attacks

Deep Mutual Information Maximin for Cross-Modal Clustering

Searching for Machine Learning Pipelines Using a Context-Free Grammar

Scalable Graph Networks for Particle Simulations

Infinite Gaussian Mixture Modeling with an Improved Estimation of the Number of Clusters

Exacerbating Algorithmic Bias through Fairness Attacks

Physarum Powered Differentiable Linear Programming Layers and Applications

Lenient Regret for Multi-Armed Bandits

Policy Optimization as Online Learning with Mediator Feedback

Consistency and Finite Sample Behavior of Binary Class Probability Estimation

Discovering Fully Oriented Causal Networks

Generative Semi-supervised Learning for Multivariate Time Series Imputation

A General Class of Transfer Learning Regression without Implementation Cost

Scheduling of Time-Varying Workloads Using Reinforcement Learning

Improved Mutual Information Estimation

Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines

Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate

Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent

Game of Gradients: Mitigating Irrelevant Clients in Federated Learning

Objective-Based Hierarchical Clustering of Deep Embedding Vectors

5* Knowledge Graph Embeddings with Projective Transformations

Advice-Guided Reinforcement Learning in a non-Markovian Environment

Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning

Modular Graph Transformer Networks for Multi-Label Image Classification

Differentially Private k-Means via Exponential Mechanism and Max Cover

Minimum Robust Multi-Submodular Cover for Fairness

Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting

An Information-Theoretic Framework for Unifying Active Learning Problems

Top-k Ranking Bayesian Optimization

Distributional Reinforcement Learning via Moment Matching

Precision-based Boosting

Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries

Learning of Structurally Unambiguous Probabilistic Grammars

RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices

Warm Starting CMA-ES for Hyperparameter Optimization

Inverse Reinforcement Learning From Like-Minded Teachers

Multinomial Logit Contextual Bandits: Provable Optimality and Practicality

Learning Deep Generative Models for Queuing Systems

OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport

FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting

Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting

Augmented Experiment in Material Engineering Using Machine Learning

Second Order Techniques for Learning Time-series with Structural Breaks

Defending against Backdoors in Federated Learning with Robust Learning Rate

Robustness Guarantees for Mode Estimation with an Application to Bandits

Disentangled Information Bottleneck

NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search

Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation

Tempered Sigmoid Activations for Deep Learning with Differential Privacy

Vector Quantized Bayesian Neural Network Inference for Data Streams

Maximum Roaming Multi-Task Learning

Fast PCA in 1-D Wasserstein Spaces via B-splines Representation and Metric Projection

AAAI Technical Track on Machine Learning IV

AutoDropout: Learning Dropout Patterns to Regularize Deep Networks

Fast Multi-view Discrete Clustering with Anchor Graphs

Relation-aware Graph Attention Model with Adaptive Self-adversarial Training

Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach

Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection

Online DR-Submodular Maximization: Minimizing Regret and Constraint Violation

Improving Generative Moment Matching Networks with Distribution Partition

Multiple Kernel Clustering with Kernel k-Means Coupled Graph Tensor Learning

Robust Fairness Under Covariate Shift

Shuffling Recurrent Neural Networks

Why Adversarial Interaction Creates Non-Homogeneous Patterns: A Pseudo-Reaction-Diffusion Model for Turing Instability

Adversarial Permutation Guided Node Representations for Link Prediction

Visual Transfer For Reinforcement Learning Via Wasserstein Domain Confusion

Anytime Inference with Distilled Hierarchical Neural Ensembles

Inverse Reinforcement Learning with Explicit Policy Estimates

A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization

AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment

Active Feature Selection for the Mutual Information Criterion

Learning Precise Temporal Point Event Detection with Misaligned Labels

Multi-type Disentanglement without Adversarial Training

Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks

Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions

Meta-Learning Effective Exploration Strategies for Contextual Bandits

Membership Privacy for Machine Learning Models Through Knowledge Transfer

Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation

Time Series Anomaly Detection with Multiresolution Ensemble Decoding

STL-SGD: Speeding Up Local SGD with Stagewise Communication Period

PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs

Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning

Federated Multi-Armed Bandits

Raven's Progressive Matrices Completion with Latent Gaussian Process Priors

Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization

Online Class-Incremental Continual Learning with Adversarial Shapley Value

Scalable Affinity Propagation for Massive Datasets

Interpretable Sequence Classification via Discrete Optimization

Towards Domain Invariant Single Image Dehazing

DIBS: Diversity Inducing Information Bottleneck in Model Ensembles

Differential Spectral Normalization (DSN) for PDE Discovery

UNIPoint: Universally Approximating Point Processes Intensities

Solving Common-Payoff Games with Approximate Policy Iteration

Improving Gradient Flow with Unrolled Highway Expectation Maximization

Implicit Kernel Attention

Error-Correcting Output Codes with Ensemble Diversity for Robust Learning in Neural Networks

Hierarchical Relational Inference

`Less Than One'-Shot Learning: Learning N Classes From M < N Samples

HiABP: Hierarchical Initialized ABP for Unsupervised Representation Learning

Stability and Generalization of Decentralized Stochastic Gradient Descent

TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL

PAC Learning of Causal Trees with Latent Variables

Learning Dynamics Models with Stable Invariant Sets

Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions

Explicitly Modeled Attention Maps for Image Classification

Proxy Graph Matching with Proximal Matching Networks

Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks

Empowering Adaptive Early-Exit Inference with Latency Awareness

Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction

Gradient Descent Averaging and Primal-dual Averaging for Strongly Convex Optimization

Evolutionary Approach for AutoAugment Using the Thermodynamical Genetic Algorithm

Semi-Supervised Knowledge Amalgamation for Sequence Classification

Online Non-Monotone DR-Submodular Maximization

Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain

Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration

Meta Learning for Causal Direction

Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior

Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems

Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods

Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach

Learning Adjustment Sets from Observational and Limited Experimental Data

*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task

Toward Robust Long Range Policy Transfer

Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks

Deep Fusion Clustering Network

ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare

Expected Eligibility Traces

Continual General Chunking Problem and SyncMap

Gated Linear Networks

GraphMix: Improved Training of GNNs for Semi-Supervised Learning

PID-Based Approach to Adversarial Attacks

Nearest Neighbor Classifier Embedded Network for Active Learning

Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning

Approximate Multiplication of Sparse Matrices with Limited Space

Projection-free Online Learning in Dynamic Environments

Projection-free Online Learning over Strongly Convex Sets

Multi-View Information-Bottleneck Representation Learning

Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks

Quantum Exploration Algorithms for Multi-Armed Bandits

Learning from Noisy Labels with Complementary Loss Functions

Debiasing Evaluations That Are Biased by Evaluations

Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion

Consistency Regularization with High-dimensional Non-adversarial Source-guided Perturbation for Unsupervised Domain Adaptation in Segmentation

Embedding Heterogeneous Networks into Hyperbolic Space Without Meta-path

Adversarial Linear Contextual Bandits with Graph-Structured Side Observations

Addressing Class Imbalance in Federated Learning

Contrastive Transformation for Self-supervised Correspondence Learning

Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model

Learning with Group Noise

Adaptive Verifiable Training Using Pairwise Class Similarity

Adaptive Algorithms for Multi-armed Bandit with Composite and Anonymous Feedback

Harmonized Dense Knowledge Distillation Training for Multi-Exit Architectures

Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters

Deep Recurrent Belief Propagation Network for POMDPs

Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis

Incremental Embedding Learning via Zero-Shot Translation

Gene Regulatory Network Inference as Relaxed Graph Matching

Unified Tensor Framework for Incomplete Multi-view Clustering and Missing-view Inferring

AAAI Technical Track on Machine Learning V

Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases

BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search

Peer Collaborative Learning for Online Knowledge Distillation

Self-Supervised Attention-Aware Reinforcement Learning

Training Spiking Neural Networks with Accumulated Spiking Flow

Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients

Fine-grained Generalization Analysis of Vector-Valued Learning

Frugal Optimization for Cost-related Hyperparameters

Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models

Curriculum-Meta Learning for Order-Robust Continual Relation Extraction

Fractal Autoencoders for Feature Selection

Neural Architecture Search as Sparse Supernet

Learning to Purify Noisy Labels via Meta Soft Label Corrector

Near-Optimal MNL Bandits Under Risk Criteria

Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning

Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science

Distant Transfer Learning via Deep Random Walk

Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation

Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler

Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation

Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling

Variational Disentanglement for Rare Event Modeling

Step-Ahead Error Feedback for Distributed Training with Compressed Gradient

Isolation Graph Kernel

Multi-Task Recurrent Modular Networks

Learning Graphons via Structured Gromov-Wasserstein Barycenters

Towards Generalized Implementation of Wasserstein Distance in GANs

Towards Feature Space Adversarial Attack by Style Perturbation

MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records

Deep Frequency Principle Towards Understanding Why Deeper Learning Is Faster

Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective

Toward Understanding the Influence of Individual Clients in Federated Learning

Adversarial Partial Multi-Label Learning with Label Disambiguation

Near Lossless Transfer Learning for Spiking Neural Networks

DeHiB: Deep Hidden Backdoor Attack on Semi-supervised Learning via Adversarial Perturbation

Robust Bandit Learning with Imperfect Context

Hierarchical Graph Capsule Network

FracBits: Mixed Precision Quantization via Fractional Bit-Widths

On Convergence of Gradient Expected Sarsa(位)

Sample Complexity of Policy Gradient Finding Second-Order Stationary Points

WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning

Characterizing the Evasion Attackability of Multi-label Classifiers

SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Task Cooperation for Semi-Supervised Few-Shot Learning

Amata: An Annealing Mechanism for Adversarial Training Acceleration

Sequential Generative Exploration Model for Partially Observable Reinforcement Learning

Enhanced Audio Tagging via Multi- to Single-Modal Teacher-Student Mutual Learning

Image-to-Image Retrieval by Learning Similarity between Scene Graphs

Learning Interpretable Models for Coupled Networks Under Domain Constraints

Identity-aware Graph Neural Networks

How Does Data Augmentation Affect Privacy in Machine Learning?

DAST: Unsupervised Domain Adaptation in Semantic Segmentation Based on Discriminator Attention and Self-Training

Any-Precision Deep Neural Networks

Personalized Adaptive Meta Learning for Cold-start User Preference Prediction

Measuring Dependence with Matrix-based Entropy Functional

Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysis

Knowledge-Guided Object Discovery with Acquired Deep Impressions

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks

Contrastive Self-supervised Learning for Graph Classification

Data-driven Competitive Algorithms for Online Knapsack and Set Cover

A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method

CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting

Exploration by Maximizing Renyi Entropy for Reward-Free RL Framework

Efficient Folded Attention for Medical Image Reconstruction and Segmentation

Interpreting Multivariate Shapley Interactions in DNNs

Sample Efficient Reinforcement Learning with REINFORCE

Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating

Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning

Deep Wasserstein Graph Discriminant Learning for Graph Classification

Treatment Effect Estimation with Disentangled Latent Factors

Regret Bounds for Online Kernel Selection in Continuous Kernel Space

The Sample Complexity of Teaching by Reinforcement on Q-Learning

Partial-Label and Structure-constrained Deep Coupled Factorization Network

Memory-Gated Recurrent Networks

Towards Enabling Learnware to Handle Unseen Jobs

Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning

Looking Wider for Better Adaptive Representation in Few-Shot Learning

Distilling Localization for Self-Supervised Representation Learning

Exploratory Machine Learning with Unknown Unknowns

Efficient Classification with Adaptive KNN

Data Augmentation for Graph Neural Networks

Augmenting Policy Learning with Routines Discovered from a Single Demonstration

Improved Consistency Regularization for GANs

Flow-based Generative Models for Learning Manifold to Manifold Mappings

Meta Label Correction for Noisy Label Learning

Going Deeper With Directly-Trained Larger Spiking Neural Networks

Fully-Connected Tensor Network Decomposition and Its Application to Higher-Order Tensor Completion

How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?

Multi-task Learning by Leveraging the Semantic Information

MetaAugment: Sample-Aware Data Augmentation Policy Learning

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Inverse Reinforcement Learning with Natural Language Goals

Tri-level Robust Clustering Ensemble with Multiple Graph Learning

Fairness in Forecasting and Learning Linear Dynamical Systems

Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance

Local Differential Privacy for Bayesian Optimization

A Primal-Dual Online Algorithm for Online Matching Problem in Dynamic Environments

Graph Neural Networks with Heterophily

Bias and Variance of Post-processing in Differential Privacy

Self-correcting Q-learning

An Efficient Algorithm for Deep Stochastic Contextual Bandits

Variational Fair Clustering

Learning Task-Distribution Reward Shaping with Meta-Learning

AAAI Technical Track on Multiagent Systems

Improving Continuous-time Conflict Based Search

Inference-Based Deterministic Messaging For Multi-Agent Communication

Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances

Learning to Resolve Conflicts for Multi-Agent Path Finding with Conflict-Based Search

The Influence of Memory in Multi-Agent Consensus

Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory

Lifelong Multi-Agent Path Finding in Large-Scale Warehouses

Dec-SGTS: Decentralized Sub-Goal Tree Search for Multi-Agent Coordination

Expected Value of Communication for Planning in Ad Hoc Teamwork

Time-Independent Planning for Multiple Moving Agents

Resilient Multi-Agent Reinforcement Learning with Adversarial Value Decomposition

Anytime Heuristic and Monte Carlo Methods for Large-Scale Simultaneous Coalition Structure Generation and Assignment

Newton Optimization on Helmholtz Decomposition for Continuous Games

Synchronous Dynamical Systems on Directed Acyclic Graphs: Complexity and Algorithms

Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games

Value-Decomposition Multi-Agent Actor-Critics

Contract-based Inter-user Usage Coordination in Free-floating Car Sharing

Maintenance of Social Commitments in Multiagent Systems

Efficient Querying for Cooperative Probabilistic Commitments

Coordination Between Individual Agents in Multi-Agent Reinforcement Learning

AAAI Technical Track on Philosophy and Ethics of AI

Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach

Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork

TripleTree: A Versatile Interpretable Representation of Black Box Agents and their Environments

Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example

FIMAP: Feature Importance by Minimal Adversarial Perturbation

Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise

Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels

A Unified Taylor Framework for Revisiting Attribution Methods

Verifiable Machine Ethics in Changing Contexts

Epistemic Logic of Know-Who

Agent Incentives: A Causal Perspective

Individual Fairness in Kidney Exchange Programs

Fair Representations by Compression

Amnesiac Machine Learning

On the Verification of Neural ODEs with Stochastic Guarantees

PenDer: Incorporating Shape Constraints via Penalized Derivatives

Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization

Differentially Private Clustering via Maximum Coverage

Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization

On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning

How RL Agents Behave When Their Actions Are Modified

Outlier Impact Characterization for Time Series Data

Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations

Ethical Dilemmas in Strategic Games

Comprehension and Knowledge

Fair Influence Maximization: a Welfare Optimization Approach

Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature Aggregation

Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption

Ethically Compliant Sequential Decision Making

Improving Robustness to Model Inversion Attacks via Mutual Information Regularization

Tightening Robustness Verification of Convolutional Neural Networks with Fine-Grained Linear Approximation

Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors

i-Algebra: Towards Interactive Interpretability of Deep Neural Networks

Decision-Guided Weighted Automata Extraction from Recurrent Neural Networks

AAAI Technical Track on Planning, Routing, and Scheduling

Computing Plan-Length Bounds Using Lengths of Longest Paths

Constrained Risk-Averse Markov Decision Processes

Contract Scheduling With Predictions

Responsibility Attribution in Parameterized Markovian Models

Symbolic Search for Optimal Total-Order HTN Planning

A Multivariate Complexity Analysis of the Material Consumption Scheduling Problem

General Policies, Representations, and Planning Width

Successor Feature Sets: Generalizing Successor Representations Across Policies

GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling

Robust Finite-State Controllers for Uncertain POMDPs

Learning General Planning Policies from Small Examples Without Supervision

Revisiting Dominance Pruning in Decoupled Search

Equitable Scheduling on a Single Machine

Landmark Generation in HTN Planning

Endomorphisms of Classical Planning Tasks

Bike-Repositioning Using Volunteers: Crowd Sourcing with Choice Restriction

Branch and Price for Bus Driver Scheduling with Complex Break Constraints

On-line Learning of Planning Domains from Sensor Data in PAL: Scaling up to Large State Spaces

Progression Heuristics for Planning with Probabilistic LTL Constraints

Bayesian Optimized Monte Carlo Planning

Improved POMDP Tree Search Planning with Prioritized Action Branching

Synthesis of Search Heuristics for Temporal Planning via Reinforcement Learning

Revealing Hidden Preconditions and Effects of Compound HTN Planning Tasks 鈥?A Complexity Analysis

Faster and Better Simple Temporal Problems

Latent Independent Excitation for Generalizable Sensor-based Cross-Person Activity Recognition

Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes

An LP-Based Approach for Goal Recognition as Planning

Saturated Post-hoc Optimization for Classical Planning

Improved Knowledge Modeling and Its Use for Signaling in Multi-Agent Planning with Partial Observability

Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks

Symbolic Search for Oversubscription Planning

Online Action Recognition

A Complexity-theoretic Analysis of Green Pickup-and-Delivery Problems

Faster Stackelberg Planning via Symbolic Search and Information Sharing

On the Optimal Efficiency of A* with Dominance Pruning

Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search

Asking the Right Questions: Learning Interpretable Action Models Through Query Answering

Competitive Analysis for Two-Level Ski-Rental Problem

Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems

AAAI Technical Track on Reasoning under Uncertainty

Group Fairness by Probabilistic Modeling with Latent Fair Decisions

GO Hessian for Expectation-Based Objectives

Better Bounds on the Adaptivity Gap of Influence Maximization under Full-adoption Feedback

Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks

Scalable First-Order Methods for Robust MDPs

High Dimensional Level Set Estimation with Bayesian Neural Network

A Generative Adversarial Framework for Bounding Confounded Causal Effects

Estimating Identifiable Causal Effects through Double Machine Learning

Relational Boosted Bandits

Instrumental Variable-based Identification for Causal Effects using Covariate Information

Learning Continuous High-Dimensional Models using Mutual Information and Copula Bayesian Networks

Submodel Decomposition Bounds for Influence Diagrams

A New Bounding Scheme for Influence Diagrams

Estimation of Spectral Risk Measures

Probabilistic Dependency Graphs

Robust Contextual Bandits via Bootstrapping

Learning the Parameters of Bayesian Networks from Uncertain Data

Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs

Bounding Causal Effects on Continuous Outcome

AAAI Technical Track on Search and Optimization

A Fast Exact Algorithm for the Resource Constrained Shortest Path Problem

Generalization in Portfolio-Based Algorithm Selection

Combining Preference Elicitation with Local Search and Greedy Search for Matroid Optimization

f-Aware Conflict Prioritization & Improved Heuristics For Conflict-Based Search

Parameterized Algorithms for MILPs with Small Treedepth

NuQClq: An Effective Local Search Algorithm for Maximum Quasi-Clique Problem

Symmetry Breaking for k-Robust Multi-Agent Path Finding

Escaping Local Optima with Non-Elitist Evolutionary Algorithms

Pareto Optimization for Subset Selection with Dynamic Partition Matroid Constraints

Theoretical Analyses of Multi-Objective Evolutionary Algorithms on Multi-Modal Objectives

Multi-Objective Submodular Maximization by Regret Ratio Minimization with Theoretical Guarantee

Choosing the Initial State for Online Replanning

OpEvo: An Evolutionary Method for Tensor Operator Optimization

Efficient Bayesian Network Structure Learning via Parameterized Local Search on Topological Orderings

Enhancing Balanced Graph Edge Partition with Effective Local Search

Submodular Span, with Applications to Conditional Data Summarization

EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Finding

Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems

Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model

Policy-Guided Heuristic Search with Guarantees

Deep Innovation Protection: Confronting the Credit Assignment Problem in Training Heterogeneous Neural Architectures

Weighting-based Variable Neighborhood Search for Optimal Camera Placement

Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering

Bayes DistNet - A Robust Neural Network for Algorithm Runtime Distribution Predictions

Learning Branching Heuristics for Propositional Model Counting

Accelerated Combinatorial Search for Outlier Detection with Provable Bound on Sub-Optimality

Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem

Improving Maximum k-plex Solver via Second-Order Reduction and Graph Color Bounding

AAAI Technical Track on Speech and Natural Language Processing I

GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extraction

Empirical Regularization for Synthetic Sentence Pairs in Unsupervised Neural Machine Translation

Segmentation of Tweets with URLs and its Applications to Sentiment Analysis

Unsupervised Opinion Summarization with Content Planning

Enhancing Scientific Papers Summarization with Citation Graph

Multi-Dimensional Explanation of Target Variables from Documents

Joint Semantic Analysis with Document-Level Cross-Task Coherence Rewards

Segatron: Segment-Aware Transformer for Language Modeling and Understanding

Learning to Copy Coherent Knowledge for Response Generation

Contextualized Rewriting for Text Summarization

Knowledge-driven Natural Language Understanding of English Text and its Applications

One SPRING to Rule Them Both: Symmetric AMR Semantic Parsing and Generation without a Complex Pipeline

Benchmarking Knowledge-Enhanced Commonsense Question Answering via Knowledge-to-Text Transformation

Multilingual Transfer Learning for QA using Translation as Data Augmentation

Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision

Brain Decoding Using fNIRS

Extracting Zero-shot Structured Information from Form-like Documents: Pretraining with Keys and Triggers

Simple or Complex? Learning to Predict Readability of Bengali Texts

Lexically Constrained Neural Machine Translation with Explicit Alignment Guidance

Aspect-Level Sentiment-Controllable Review Generation with Mutual Learning Framework

Weakly-Supervised Hierarchical Models for Predicting Persuasive Strategies in Good-faith Textual Requests

A Lightweight Neural Model for Biomedical Entity Linking

Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extraction

Empower Distantly Supervised Relation Extraction with Collaborative Adversarial Training

Reasoning in Dialog: Improving Response Generation by Context Reading Comprehension

Meta-Transfer Learning for Low-Resource Abstractive Summarization

Adaptive Prior-Dependent Correction Enhanced Reinforcement Learning for Natural Language Generation

How Linguistically Fair Are Multilingual Pre-Trained Language Models?

DirectQE: Direct Pretraining for Machine Translation Quality Estimation

We Can Explain Your Research in Layman's Terms: Towards Automating Science Journalism at Scale

Consecutive Decoding for Speech-to-text Translation

Listen, Understand and Translate: Triple Supervision Decouples End-to-end Speech-to-text Translation

MultiTalk: A Highly-Branching Dialog Testbed for Diverse Conversations

Knowledge-aware Leap-LSTM: Integrating Prior Knowledge into Leap-LSTM towards Faster Long Text Classification

FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding

Rethinking Boundaries: End-To-End Recognition of Discontinuous Mentions with Pointer Networks

Encoder-Decoder Based Unified Semantic Role Labeling with Label-Aware Syntax

End-to-end Semantic Role Labeling with Neural Transition-based Model

Multi-View Feature Representation for Dialogue Generation with Bidirectional Distillation

More the Merrier: Towards Multi-Emotion and Intensity Controllable Response Generation

LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding

Nested Named Entity Recognition with Partially-Observed TreeCRFs

A Theoretical Analysis of the Repetition Problem in Text Generation

Paragraph-level Commonsense Transformers with Recurrent Memory

Judgment Prediction via Injecting Legal Knowledge into Neural Networks

Question-Driven Span Labeling Model for Aspect-Opinion Pair Extraction

Analogy Training Multilingual Encoders

Fake it Till You Make it: Self-Supervised Semantic Shifts for Monolingual Word Embedding Tasks

Perception Score: A Learned Metric for Open-ended Text Generation Evaluation

DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances

Read, Retrospect, Select: An MRC Framework to Short Text Entity Linking

Label Confusion Learning to Enhance Text Classification Models

Iterative Utterance Segmentation for Neural Semantic Parsing

BERT & Family Eat Word Salad: Experiments with Text Understanding

Sketch and Customize: A Counterfactual Story Generator

Self-Attention Attribution: Interpreting Information Interactions Inside Transformer

Humor Knowledge Enriched Transformer for Understanding Multimodal Humor

Synchronous Interactive Decoding for Multilingual Neural Machine Translation

Show Me How To Revise: Improving Lexically Constrained Sentence Generation with XLNet

Towards Fully Automated Manga Translation

SMART: A Situation Model for Algebra Story Problems via Attributed Grammar

It Takes Two to Empathize: One to Seek and One to Provide

C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot Filling

Few-shot Learning for Multi-label Intent Detection

HARGAN: Heterogeneous Argument Attention Network for Persuasiveness Prediction

SARG: A Novel Semi Autoregressive Generator for Multi-turn Incomplete Utterance Restoration

Entity Guided Question Generation with Contextual Structure and Sequence Information Capturing

Story Ending Generation with Multi-Level Graph Convolutional Networks over Dependency Trees

Adaptive Beam Search Decoding for Discrete Keyphrase Generation

Distribution Matching for Rationalization

Audio-Oriented Multimodal Machine Comprehension via Dynamic Inter- and Intra-modality Attention

Unsupervised Learning of Discourse Structures using a Tree Autoencoder

Dynamic Hybrid Relation Exploration Network for Cross-Domain Context-Dependent Semantic Parsing

DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues

Flexible Non-Autoregressive Extractive Summarization with Threshold: How to Extract a Non-Fixed Number of Summary Sentences

EQG-RACE: Examination-Type Question Generation

Hierarchical Macro Discourse Parsing Based on Topic Segmentation

FIXMYPOSE: Pose Correctional Captioning and Retrieval

Self-supervised Pre-training and Contrastive Representation Learning for Multiple-choice Video QA

The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets

SALNet: Semi-supervised Few-Shot Text Classification with Attention-based Lexicon Construction

Multi-SpectroGAN: High-Diversity and High-Fidelity Spectrogram Generation with Adversarial Style Combination for Speech Synthesis

AAAI Technical Track on Speech and Natural Language Processing II

Have We Solved The Hard Problem? It Not Easy! Contextual Lexical Contrast as a Means to Probe Neural Coherence

Learning Light-Weight Translation Models from Deep Transformer

Improving the Efficiency and Effectiveness for BERT-based Entity Resolution

Multi-view Inference for Relation Extraction with Uncertain Knowledge

Towards Topic-Aware Slide Generation For Academic Papers With Unsupervised Mutual Learning

The Style-Content Duality of Attractiveness: Learning to Write Eye-Catching Headlines via Disentanglement

ACT: an Attentive Convolutional Transformer for Efficient Text Classification

Quantum-inspired Neural Network for Conversational Emotion Recognition

HopRetriever: Retrieve Hops over Wikipedia to Answer Complex Questions

Merging Statistical Feature via Adaptive Gate for Improved Text Classification

TSQA: Tabular Scenario Based Question Answering

Interpretable NLG for Task-oriented Dialogue Systems with Heterogeneous Rendering Machines

An Efficient Transformer Decoder with Compressed Sub-layers

An Unsupervised Sampling Approach for Image-Sentence Matching Using Document-level Structural Information

Finding Sparse Structures for Domain Specific Neural Machine Translation

Infusing Multi-Source Knowledge with Heterogeneous Graph Neural Network for Emotional Conversation Generation

Hierarchical Coherence Modeling for Document Quality Assessment

Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation

Neural Sentence Simplification with Semantic Dependency Information

Converse, Focus and Guess - Towards Multi-Document Driven Dialogue

Natural Language Inference in Context - Investigating Contextual Reasoning over Long Texts

How to Train Your Agent to Read and Write

Filling the Gap of Utterance-aware and Speaker-aware Representation for Multi-turn Dialogue

Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View

Faster Depth-Adaptive Transformers

A Graph Reasoning Network for Multi-turn Response Selection via Customized Pre-training

Generating CCG Categories

CrossNER: Evaluating Cross-Domain Named Entity Recognition

On the Importance of Word Order Information in Cross-lingual Sequence Labeling

SCRUPLES: A Corpus of Community Ethical Judgments on 32,000 Real-Life Anecdotes

UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark

Span-Based Event Coreference Resolution

LET: Linguistic Knowledge Enhanced Graph Transformer for Chinese Short Text Matching

Knowledge-driven Data Construction for Zero-shot Evaluation in Commonsense Question Answering

Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text

Generating Natural Language Attacks in a Hard Label Black Box Setting

Bridging Towers of Multi-task Learning with a Gating Mechanism for Aspect-based Sentiment Analysis and Sequential Metaphor Identification

A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis

Variational Inference for Learning Representations of Natural Language Edits

How Robust are Model Rankings : A Leaderboard Customization Approach for Equitable Evaluation

Continual Learning for Named Entity Recognition

MASKER: Masked Keyword Regularization for Reliable Text Classification

Disentangled Motif-aware Graph Learning for Phrase Grounding

Knowledge-aware Named Entity Recognition with Alleviating Heterogeneity

Dialog Policy Learning for Joint Clarification and Active Learning Queries

The Heads Hypothesis: A Unifying Statistical Approach Towards Understanding Multi-Headed Attention in BERT

Copy That! Editing Sequences by Copying Spans

Movie Summarization via Sparse Graph Construction

On the Softmax Bottleneck of Recurrent Language Models

XL-WSD: An Extra-Large and Cross-Lingual Evaluation Framework for Word Sense Disambiguation

ALP-KD: Attention-Based Layer Projection for Knowledge Distillation

Data Augmentation for Abstractive Query-Focused Multi-Document Summarization

Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection

Conceptualized and Contextualized Gaussian Embedding

A Student-Teacher Architecture for Dialog Domain Adaptation Under the Meta-Learning Setting

Exploring Auxiliary Reasoning Tasks for Task-oriented Dialog Systems with Meta Cooperative Learning

Co-GAT: A Co-Interactive Graph Attention Network for Joint Dialog Act Recognition and Sentiment Classification

Reinforced History Backtracking for Conversational Question Answering

Guiding Non-Autoregressive Neural Machine Translation Decoding with Reordering Information

Towards Semantics-Enhanced Pre-Training: Can Lexicon Definitions Help Learning Sentence Meanings?

Automated Cross-prompt Scoring of Essay Traits

Exploring Transfer Learning For End-to-End Spoken Language Understanding

Semantics Altering Modifications for Evaluating Comprehension in Machine Reading

Learning from the Best: Rationalizing Predictions by Adversarial Information Calibration

Nutri-bullets: Summarizing Health Studies by Composing Segments

DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition

SongMASS: Automatic Song Writing with Pre-training and Alignment Constraint

Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training

A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection

Fact-Enhanced Synthetic News Generation

Improving Commonsense Causal Reasoning by Adversarial Training and Data Augmentation

Re-TACRED: Addressing Shortcomings of the TACRED Dataset

Progressive Multi-task Learning with Controlled Information Flow for Joint Entity and Relation Extraction

RpBERT: A Text-image Relation Propagation-based BERT Model for Multimodal NER

Unsupervised Learning of Deterministic Dialogue Structure with Edge-Enhanced Graph Auto-Encoder

VisualMRC: Machine Reading Comprehension on Document Images

A Bidirectional Multi-paragraph Reading Model for Zero-shot Entity Linking

Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification

Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks

FL-MSRE: A Few-Shot Learning based Approach to Multimodal Social Relation Extraction

KEML: A Knowledge-Enriched Meta-Learning Framework for Lexical Relation Classification

Exploring Explainable Selection to Control Abstractive Summarization

AAAI Technical Track on Speech and Natural Language Processing III

Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling

Effective Slot Filling via Weakly-Supervised Dual-Model Learning

Tune-In: Training Under Negative Environments with Interference for Attention Networks Simulating Cocktail Party Effect

Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation

Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsing

Generating Diversified Comments via Reader-Aware Topic Modeling and Saliency Detection

Adversarial Training with Fast Gradient Projection Method against Synonym Substitution Based Text Attacks

NaturalConv: A Chinese Dialogue Dataset Towards Multi-turn Topic-driven Conversation

Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs

Robustness to Spurious Correlations in Text Classification via Automatically Generated Counterfactuals

MLE-Guided Parameter Search for Task Loss Minimization in Neural Sequence Modeling

Do Response Selection Models Really Know What鈥檚 Next? Utterance Manipulation Strategies for Multi-turn Response Selection

On Scalar Embedding of Relative Positions in Attention Models

Evidence Inference Networks for Interpretable Claim Verification

TextGAIL: Generative Adversarial Imitation Learning for Text Generation

MELINDA: A Multimodal Dataset for Biomedical Experiment Method Classification

A Controllable Model of Grounded Response Generation

Context-Guided BERT for Targeted Aspect-Based Sentiment Analysis

Does Head Label Help for Long-Tailed Multi-Label Text Classification

Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition

Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning

Enabling Fast and Universal Audio Adversarial Attack Using Generative Model

Nystr枚mformer: A Nystr枚m-based Algorithm for Approximating Self-Attention

Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction

Learning an Effective Context-Response Matching Model with Self-Supervised Tasks for Retrieval-based Dialogues

Document-Level Relation Extraction with Reconstruction

Topic-Aware Multi-turn Dialogue Modeling

A Supervised Multi-Head Self-Attention Network for Nested Named Entity Recognition

GDPNet: Refining Latent Multi-View Graph for Relation Extraction

Human-Level Interpretable Learning for Aspect-Based Sentiment Analysis

Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric

Multi-Document Transformer for Personality Detection

UBAR: Towards Fully End-to-End Task-Oriented Dialog System with GPT-2

Open Domain Dialogue Generation with Latent Images

Adversarial Language Games for Advanced Natural Language Intelligence

Contrastive Triple Extraction with Generative Transformer

Unanswerable Question Correction in Question Answering over Personal Knowledge Base

Simpson's Bias in NLP Training

Reinforced Multi-Teacher Selection for Knowledge Distillation

What's the Best Place for an AI Conference, Vancouver or _______: Why Completing Comparative Questions is Difficult

Probing Product Description Generation via Posterior Distillation

Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation

UWSpeech: Speech to Speech Translation for Unwritten Languages

Building Interpretable Interaction Trees for Deep NLP Models

Multi-modal Multi-label Emotion Recognition with Heterogeneous Hierarchical Message Passing

Multi-modal Graph Fusion for Named Entity Recognition with Targeted Visual Guidance

Accelerating Neural Machine Translation with Partial Word Embedding Compression

Discovering New Intents with Deep Aligned Clustering

Deep Open Intent Classification with Adaptive Decision Boundary

Writing Polishment with Simile: Task, Dataset and A Neural Approach

Continuous Self-Attention Models with Neural ODE Networks

TaLNet: Voice Reconstruction from Tongue and Lip Articulation with Transfer Learning from Text-to-Speech Synthesis

Making the Relation Matters: Relation of Relation Learning Network for Sentence Semantic Matching

MERL: Multimodal Event Representation Learning in Heterogeneous Embedding Spaces

Future-Guided Incremental Transformer for Simultaneous Translation

Semantics-Aware Inferential Network for Natural Language Understanding

Learning to Check Contract Inconsistencies

Self-supervised Bilingual Syntactic Alignment for Neural Machine Translation

Graph-Based Tri-Attention Network for Answer Ranking in CQA

Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Word Embeddings and the Implications to Representation Learning

Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model

Unsupervised Abstractive Dialogue Summarization for Tete-a-Tetes

News Content Completion with Location-Aware Image Selection

Retrospective Reader for Machine Reading Comprehension

Dynamic Modeling Cross- and Self-Lattice Attention Network for Chinese NER

A Unified Multi-Task Learning Framework for Joint Extraction of Entities and Relations

LIREx: Augmenting Language Inference with Relevant Explanations

Automatic Curriculum Learning With Over-repetition Penalty for Dialogue Policy Learning

Interactive Speech and Noise Modeling for Speech Enhancement

Stylized Dialogue Response Generation Using Stylized Unpaired Texts

Keyword-Guided Neural Conversational Model

CARE: Commonsense-Aware Emotional Response Generation with Latent Concepts

MTAAL: Multi-Task Adversarial Active Learning for Medical Named Entity Recognition and Normalization

A Neural Group-wise Sentiment Analysis Model with Data Sparsity Awareness

EvaLDA: Efficient Evasion Attacks Towards Latent Dirichlet Allocation

Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling

IsoBN: Fine-Tuning BERT with Isotropic Batch Normalization

An Adaptive Hybrid Framework for Cross-domain Aspect-based Sentiment Analysis

What the Role is vs. What Plays the Role: Semi-Supervised Event Argument Extraction via Dual Question Answering

Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference

Neural Sentence Ordering Based on Constraint Graphs

Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling

Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-Encoders

AAAI Special Track on AI for Social Impact

Fairness in Influence Maximization through Randomization

Intelligent Recommendations for Citizen Science

Learning Augmented Methods for Matching: Improving Invasive Species Management and Urban Mobility

Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing

Real-time Tropical Cyclone Intensity Estimation by Handling Temporally Heterogeneous Satellite Data

Detection and Prediction of Nutrient Deficiency Stress using Longitudinal Aerial Imagery

Graph Learning for Inverse Landscape Genetics

Harnessing Social Media to Identify Homeless Youth At-Risk of Substance Use

Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users

Retrieve and Revise: Improving Peptide Identification with Similar Mass Spectra

K-N-MOMDPs: Towards Interpretable Solutions for Adaptive Management

Predicting Flashover Occurrence using Surrogate Temperature Data

Fair and Interpretable Algorithmic Hiring using Evolutionary Many Objective Optimization

Abusive Language Detection in Heterogeneous Contexts: Dataset Collection and the Role of Supervised Attention

Project RISE: Recognizing Industrial Smoke Emissions

Computational Visual Ceramicology: Matching Image Outlines to Catalog Sketches

Prediction of Landfall Intensity, Location, and Time of a Tropical Cyclone

Court Opinion Generation from Case Fact Description with Legal Basis

Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images

Mitigating Political Bias in Language Models through Reinforced Calibration

HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection

Goten: GPU-Outsourcing Trusted Execution of Neural Network Training

A Universal 2-state n-action Adaptive Management Solver

We Don't Speak the Same Language: Interpreting Polarization through Machine Translation

RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery

Combining Machine Learning & Reasoning for Biodiversity Data Intelligence

Degree Planning with PLAN-BERT: Multi-Semester Recommendation Using Future Courses of Interest

Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service

Evidence Aware Neural Pornographic Text Identification for Child Protection

Clinical Trial of an AI-Augmented Intervention for HIV Prevention in Youth Experiencing Homelessness

Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection

Multi-Layer Networks for Ensemble Precipitation Forecasts Postprocessing

Dual-Mandate Patrols: Multi-Armed Bandits for Green Security

Predicting Forest Fire Using Remote Sensing Data And Machine Learning

Early Safety Warnings for Long-Distance Pipelines: A Distributed Optical Fiber Sensor Machine Learning Approach

Joint Incentive Optimization of Customer and Merchant in Mobile Payment Marketing

Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network

HOT-VAE: Learning High-Order Label Correlation for Multi-Label Classification via Attention-Based Variational Autoencoders

Forecasting Reservoir Inflow via Recurrent Neural ODEs

Land Deformation Prediction via Slope-Aware Graph Neural Networks

Senior Member Presentation: Blue Sky Papers

Thinking Fast and Slow in AI

Towards a Unifying Framework for Formal Theories of Novelty

Improving Causal Inference by Increasing Model Expressiveness

Lifelong and Continual Learning Dialogue Systems: Learning during Conversation

Unifying Principles and Metrics for Safe and Assistive AI

Senior Member Presentation: Summary Papers

Thou Shalt Love Thy Neighbor as Thyself When Thou Playest: Altruism in Game Theory

Empowering Conversational AI is a Trip to Mars: Progress and Future of Open Domain Human-Computer Dialogues

IAAI Technical Track on Highly Innovative Applications of AI

Preclinical Stage Alzheimer's Disease Detection Using Magnetic Resonance Image Scans

An End-to-End Solution for Named Entity Recognition in eCommerce Search

Automated Reasoning and Learning for Automated Payroll Management

Comparison Lift: Bandit-based Experimentation System for Online Advertising

Accurate and Interpretable Machine Learning for Transparent Pricing of Health Insurance Plans

Robust PDF Document Conversion using Recurrent Neural Networks

Author Homepage Discovery in CiteSeerX

EeLISA: Combating Global Warming Through the Rapid Analysis of Eelgrass Wasting Disease

Deeplite NeutrinoTM: A BlackBox Framework for Constrained Deep Learning Model Optimization

Using Unsupervised Learning for Data-driven Procurement Demand Aggregation

Tool for Automated Tax Coding of Invoices

An Automated Engineering Assistant: Learning Parsers for Technical Drawings

Mars Image Content Classification: Three Years of NASA Deployment and Recent Advances

Enhancing E-commerce Recommender System Adaptability with Online Deep Controllable Learning-To-Rank

IAAI Technical Track on Emerging Applications of AI

A Novel AI-based Methodology for Identifying Cyber Attacks in Honey Pots

Finding Needles in Heterogeneous Haystacks

Path to Automating Ocean Health Monitoring

Ontology-Enriched Query Answering on Relational Databases

Attr2Style: A Transfer Learning Approach for Inferring Fashion Styles via Apparel Attributes

Topological Machine Learning Methods for Power System Responses to Contingencies

Data-Driven Multimodal Patrol Planning for Anti-poaching

Deepening the Sense of Touch in Planetary Exploration with Geometric and Topological Deep Learning

Identification of Abnormal States in Videos of Ants Undergoing Social Phase Change

Shape-based Feature Engineering for Solar Flare Prediction

JEL: Applying End-to-End Neural Entity Linking in JPMorgan Chase

Where there's Smoke, there's Fire: Wildfire Risk Predictive Modeling via Historical Climate Data

Over-MAP: Structural Attention Mechanism and Automated Semantic Segmentation Ensembled for Uncertainty Prediction

Spatiotemporal Graph Neural Network for Performance Prediction of Photovoltaic Power Systems

VRU Pose-SSD: Multiperson Pose Estimation For Automated Driving

Personalizing Individual Comfort in the Group Setting

Twitter Event Summarization by Exploiting Semantic Terms and Graph Network

Reinforcement Learning-based Product Delivery Frequency Control

SKATE: A Natural Language Interface for Encoding Structured Knowledge

Predicting Mining Industry Accidents with a Multitask Learning Approach

Using Online Planning and Acting to Recover from Cyberattacks on Software-defined Networks

A Reciprocal Embedding Framework For Modelling Mutual Preferences

DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting

Carbon to Diamond: An Incident Remediation Assistant System From Site Reliability Engineers鈥?Conversations in Hybrid Cloud Operations

Predicting Parking Availability from Mobile Payment Transactions with Positive Unlabeled Learning

Device Fabrication Knowledge Extraction from Materials Science Literature

Deep Epidemiological Modeling by Black-box Knowledge Distillation: An Accurate Deep Learning Model for COVID-19

IAAI Technical Track on Innovative Tools for Enabling AI Application

HetSeq: Distributed GPU Training on Heterogeneous Infrastructure

Representing the Unification of Text Featurization using a Context-Free Grammar

IAAI Technical Track on AI Best Practices, Challenge Problems, Training AI Users

Combining Machine Learning and Human Experts to Predict Match Outcomes in Football: A Baseline Model

Empirical Best Practices On Using Product-Specific Schema.org

Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database

EAAI Symposium: Full Papers

A Heuristic Evaluation Function for Hand Strength Estimation in Gin Rummy

What are GANs?: Introducing Generative Adversarial Networks to Middle School Students

Visualizing NLP in Undergraduate Students' Learning about Natural Language

Heisenbot: A Rule-Based Game Agent for Gin Rummy

Opponent Hand Estimation in the Game of Gin Rummy

Estimating Card Fitness for Discard in Gin Rummy

Evaluating Gin Rummy Hands Using Opponent Modeling and Myopic Meld Distance

Extracting Learned Discard and Knocking Strategies from a Gin Rummy Bot

Learning Artificial Intelligence: Insights into How Youth Encounter and Build Understanding of AI Concepts

Deep Discourse Analysis for Generating Personalized Feedback in Intelligent Tutor Systems

Random Forests for Opponent Hand Estimation in Gin Rummy

PoseBlocks: A Toolkit for Creating (and Dancing) with AI

Student Knowledge Prediction for Teacher-Student Interaction

Why and What to Teach: AI Curriculum for Elementary School

Modeling Expert Knowledge in a Heuristic-Based Gin Rummy Agent

The Contour to Classification Game

AI-Infused Collaborative Inquiry in Upper Elementary School: A Game-Based Learning Approach

Knocking in the Game of Gin Rummy

Opponent Hand Estimation in Gin Rummy Using Deep Neural Networks and Heuristic Strategies

A Highly-Parameterized Ensemble to Play Gin Rummy

A Deterministic Neural Network Approach to Playing Gin Rummy

Introduction to Machine Learning with Robots and Playful Learning

Designing a Hybrid AI Residency

A Data-Driven Approach for Gin Rummy Hand Evaluation

Teaching Tech to Talk: K-12 Conversational Artificial Intelligence Literacy Curriculum and Development Tools

GANs Unplugged

Educational Question Mining At Scale: Prediction, Analysis and Personalization

Teacher Perspectives on How To Train Your Robot: A Middle School AI and Ethics Curriculum

Web-based Platform for K-12 AI Education in China

Applied Machine Learning for Games: A Graduate School Course

EAAI Symposium: Model AI Assignment Abstracts

Model AI Assignments 2021

The Twenty-Sixth AAAI/SIGAI Doctoral Consortium

A Computational Approach to Sign Language Understanding

Effective Clustering of scRNA-seq Data to Identify Biomarkers without User Input

Creating Interpretable Data-Driven Approaches for Remote Health Monitoring

Verification and Repair of Neural Networks

Perception Beyond Sensors Under Uncertainty

Artificial Intelligence and Machine Learning for Autonomous Agents that Learn to Plan and Operate in Unpredictable Dynamic Environments

On Learning Deep Models with Imbalanced Data Distribution

Screening for Depressed Individuals by Using Multimodal Social Media Data

Relational Learning to Capture the Dynamics and Sparsity of Knowledge Graphs

Constraint-Driven Learning of Logic Programs

Transfer Learning of Engagement Recognition within Robot-Assisted Therapy for Children with Autism

Robots that Help Humans Build Better Mental Models of Robots

AI for Social Good: Between My Research and the Real World

Safety Assurance for Systems with Machine Learning Components

Towards Fair, Equitable, and Efficient Peer Review

Multi-agent Reinforcement Learning for Decentralized Coalition Formation Games

Distributed Situation Awareness for Multi-agent Mission in Dynamic Environments: A Case Study of Multi-UAVs Wildfires Searching

How Human Centered AI Will Contribute Towards Intelligent Gaming Systems

AAAI Student Abstract and Poster Program

Role of Optimizer on Network Fine-tuning for Adversarial Robustness (Student Abstract)

A Serverless Approach to Federated Learning Infrastructure Oriented for IoT/Edge Data Sources (Student Abstract)

Reward based Hebbian Learning in Direct Feedback Alignment (Student Abstract)

Clustering Partial Lexicographic Preference Trees (Student Abstract)

Logic Guided Genetic Algorithms (Student Abstract)

Responsible Prediction Making of COVID-19 Mortality (Student Abstract)

Encoding Temporal and Spatial Vessel Context using Self-Supervised Learning Model (Student Abstract)

Unsupervised Causal Knowledge Extraction from Text using Natural Language Inference (Student Abstract)

Early Prediction of Children鈥檚 Task Completion in a Tablet Tutor using Visual Features (Student Abstract)

Fair Stable Matchings Under Correlated Preferences (Student Abstract)

BOSS: A Bi-directional Search Technique for Optimal Coalition Structure Generation with Minimal Overlapping (Student Abstract)

NEAP-F: Network Epoch Accuracy Prediction Framework (Student Abstract)

Robotic Manipulation with Reinforcement Learning, State Representation Learning, and Imitation Learning (Student Abstract)

Multi-modal User Intent Classification Under the Scenario of Smart Factory (Student Abstract)

Passive learning of Timed Automata from logs (Student Abstract)

Reducing Neural Network Parameter Initialization Into an SMT Problem (Student Abstract)

Incorporating Curiosity into Personalized Ranking for Collaborative Filtering (Student Abstract)

Demonstrating the Equivalence of List Based and Aggregate Metrics to Measure the Diversity of Recommendations (Student Abstract)

Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement (Student Abstract)

Detecting Lexical Semantic Change across Corpora with Smooth Manifolds (Student Abstract)

Evaluating Meta-Reinforcement Learning through a HVAC Control Benchmark (Student Abstract)

RGB-D Scene Recognition based on Object-Scene Relation (Student Abstract)

Global Fusion Attention for Vision and Language Understanding (Student Abstract)

Text Embedding Bank for Detailed Image Paragraph Captioning

Reinforcement Based Learning on Classification Task Yields Better Generalization and Adversarial Accuracy (Student Abstract)

Pedestrian's Intention Recognition, Fusion of Handcrafted Features in a Deep Learning Approach

EC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANs (Student Abstract)

Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract)

Dethroning Aristocracy in Graphs via Adversarial Perturbations (Student Abstract)

HetSAGE: Heterogenous Graph Neural Network for Relational Learning (Student Abstract)

Rotation-Invariant Gait Identification with Quaternion Convolutional Neural Networks (Student Abstract)

Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks

Compilation Complexity of Multi-Winner Voting Rules (Student Abstract)

A Deep Learning Framework for Improving Lameness Identification in Dairy Cattle

An Unfair Affinity Toward Fairness: Characterizing 70 Years of Social Biases in BHollywood (Student Abstract)

Leveraging on Deep Reinforcement Learning for Autonomous Safe Decision-Making in Highway On-ramp Merging (Student Abstract)

Robustness to Missing Features using Hierarchical Clustering with Split Neural Networks (Student Abstract)

Is Active Learning Always Beneficial? (Student Abstract)

Domain Generalisation with Domain Augmented Supervised Contrastive Learning (Student Abstract)

A Nested Named Entity Recognition Model Based on Multi-agent Communication Mechanism (Student Abstract)

Melodic Phrase Attention Network for Symbolic Data-based Music Genre Classification (Student Abstract)

Towards Sample Efficient Agents through Algorithmic Alignment (Student Abstract)

Information Block Detection in Infographic Based on Spatial Proximity and Structural Similarity (Student Abstract)

A Quantum-inspired Complex-valued Representation for Encoding Sentiment Information (Student Abstract)

An Attention Based Multi-view Model for Sarcasm Cause Detection (Student Abstract)

Semi-Discrete Social Recommendation (Student Abstract)

Generating Adversarial yet Inconspicuous Patches with a Single Image (Student Abstract)

A Context Aware Approach for Generating Natural Language Attacks

RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract)

Improving the Performance-Compatibility Tradeoff with Personalized Objective Functions (Student Abstract)

Detection of Digital Manipulation in Facial Images (Student Abstract)

Source Separation and Depthwise Separable Convolutions for Computer Audition (Student Abstract)

Toward Determining NFA Equivalence via QBFs (Student Abstract)

Two-Sided Fairness in Non-Personalised Recommendations (Student Abstract)

Shallow-UWnet: Compressed Model for Underwater Image Enhancement (Student Abstract)

Improving Label Noise Robustness with Data Augmentation and Semi-Supervised Learning (Student Abstract)

Deep Reinforcement Learning for a Dictionary Based Compression Schema (Student Abstract)

A Method for Taxonomy-Aware Embeddings Evaluation (Student Abstract)

Solving JumpIN鈥?Using Zero-Dependency Reinforcement Learning (Student Abstract)

Preventing Overfitting via Sample Reweighting for Recommender System Incremental Update (Student Abstract)

An Entity-Aware Adversarial Domain Adaptation Network for Cross-Domain Named Entity Recognition (Student Abstract)

Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning (Student Abstract)

Successive Halving Top-k Operator

Context-Enhanced Entity and Relation Embedding for Knowledge Graph Completion (Student Abstract)

AuthNet: A Deep Learning Based Authentication Mechanism Using Temporal Facial Feature Movements (Student Abstract)

SSA2D: Single Shot Actor-Action Detection in Videos (Student Abstract)

Automatic Optimal Multi-Agent Path Finding Algorithm Selector (Student Abstract)

Generating Long Financial Report using Conditional Variational Autoencoders with Knowledge Distillation

Are Chess Discussions Racist? An Adversarial Hate Speech Data Set (Student Abstract)

Data Domain Change and Feature Selection to Predict Cardiac Pathology with a 2D Clinical Dataset and Convolutional Neural Networks (Student Abstract)

Skills2Job: A Recommender System that Encodes Job Offer Embeddings on Graph Databases (Student Abstract)

Attention Beam: An Image Captioning Approach (Student Abstract)

Quantum Binary Classification (Student Abstract)

Neuro-Symbolic Techniques for Description Logic Reasoning (Student Abstract)

Mental Actions and Explainability in Kripkean Semantics: What Else do I Know? (Student Abstract)

Learning to Enhance Visual Quality via Hyperspectral Domain Mapping (Student Abstract)

SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract)

Scalable Partial Explainability in Neural Networks via Flexible Activation Functions (Student Abstract)

Sampling Partial Acyclic Orientations in Chordal Graphs by the Lovasz Local Lemma (Student Abstract)

Semi-Supervised Learning via Triplet Network Based Active Learning (Student Abstract)

WildfireNet: Predicting Wildfire Profiles (Student Abstract)

FACS: Fast Code-based Algorithm for Coalition Structure Generation (Student Abstract)

Mining Intelligent Patterns using SVAC for Precision Agriculture and Optimizing Irrigation (Student Abstract)

A New Robust Subspace Recovery Algorithm (Student Abstract)

Chinese Character Image Clustering and Classification Based on Object Embedding Model (Student Abstract)

Is Each Layer Non-trivial in CNN? (Student Abstract)

Multi-label Few-shot Learning with Semantic Inference (Student Abstract)

Extending Policy Shaping to Continuous State Spaces (Student Abstract)

Measuring Vegetation Density in Marsh Grass Photographs Using Deep Neural Networks (Student Abstract)

Remember More by Recalling Less: Investigating the Role of Batch Size in Continual Learning with Experience Replay (Student Abstract)

Towards Extracting Graph Neural Network Models via Prediction Queries (Student Abstract)

LB-DESPOT: Efficient Online POMDP Planning Considering Lower Bound in Action Selection (Student Abstract)

Local Search for Diversified Top-k s-plex Search Problem (Student Abstract)

A Double Phases Generation Network for Yes or No Question Generation (Student Abstract)

MMIM: An Interpretable Regularization Method for Neural Networks (Student Abstract)

Change or Not: A Simple Approach for Plug and Play Language Models on Sentiment Control

Enhancing Context-Based Meta-Reinforcement Learning Algorithms via An Efficient Task Encoder (Student Abstract)

Improving the Morphology and Control Policy of Self-reconfiguring Modular Robots in Dynamic Environment (Student Abstract)

Zera-Shot Sentiment Analysis for Code-Mixed Data

Contextual Bandits with Delayed Feedback and Semi-supervised Learning (Student Abstract)

Modeling High-order Interactions across Multi-interests for Micro-video Reommendation (Student Abstract)

Incorporating Bidirection-Interactive Information and Semantic Features for Relational Facts Extraction (Student Abstract)

LAMS: A Location-aware Approach for Multimodal Summarization (Student Abstract)

Knowledge-aware Dialogue Generation with Hybrid Attention (Student Abstract)

State-Wise Adaptive Discounting from Experience (SADE): A Novel Discounting Scheme for Reinforcement Learning (Student Abstract)

AAAI Undergraduate Consortium

Evolving Spiking Circuit Motifs Using Weight Agnostic Neural Networks

Text Analysis for Understanding Symptoms of Social Anxiety in Student Veterans

Analyzing Games with a Variable Number of Players

Using Remote Sensing Imagery and Machine Learning to Predict Poaching in Wildlife Conservation Parks

The Price of Anarchy in ROSCAS with Risk Averse Agents

Probabilistic Robustness Quantification of Neural Networks

Affect-Aware Machine Learning Models for Deception Detection

Exploration of Unknown Environments Using Deep Reinforcement Learning

Efficient Robust Music Genre Classification with Depthwise Separable Convolutions and Source Separation

Use of Computer Vision to Develop a Device to Assist Visually Impaired People with Social Distance.

Predictive Agent-Based Modeling of Natural Disasters Using Machine Learning

Investigating Methods of Balancing Inequality and Efficiency in Ride Pooling

MOTIF-Driven Contrastive Learning of Graph Representations

Bison Hacks the Yard: Assisting Underrepresented Students Overcome Impostor Syndrome with Augmented Reality and Artificial Intelligence

AAAI Demonstration Track

A Semantic Parsing and Reasoning-Based Approach to Knowledge Base Question Answering

Exploring the Efficacy of Generic Drugs in Treating Cancer

OzoMorph: Demonstrating Colored Multi-Agent Path Finding on Real Robots

VEGA: a Virtual Environment for Exploring Gender Bias vs. Accuracy Trade-offs in AI Translation Services

A Compression-Compilation Co-Design Framework Towards Real-Time Object Detection on Mobile Devices

AutoText: An End-to-End AutoAI Framework for Text

A Health-friendly Speaker Verification System Supporting Mask Wearing

An Intelligent Assistant for Problem Behavior Management

OPRA: An Open-Source Online Preference Reporting and Aggregation System

ESO-MAPF: Bridging Discrete Planning and Continuous Execution in Multi-Agent Pathfinding

Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback

Juice: A Julia Package for Logic and Probabilistic Circuits

Bootstrapping Dialog Models from Human to Human Conversation Logs

Doc2Bot: Document grounded Bot Framework

KAAPA: Knowledge Aware Answers from PDF Analysis

IBM Scenario Planning Advisor: A Neuro-Symbolic ERM Solution

NEO: A System for Identifying New Emerging Occupation from Job Ads

Dialog Router: Automated Dialog Transition via Multi-Task Learning

EasyRL: A Simple and Extensible Reinforcement Learning Framework

AI-Empowered Decision Support for COVID-19 Social Distancing

Mobile-based Clock Drawing Test for Detecting Early Signs of Dementia

RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions

Business Entity Matching with Siamese Graph Convolutional Networks

Democratizing Constraint Satisfaction Problems through Machine Learning

TODS: An Automated Time Series Outlier Detection System

Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains (Demo)

Interactive Video Object Mask Annotation

CamouFinder: Finding Camouflaged Instances in Images

A Novel Mountain Driving Unity Simulated Environment for Autonomous Vehicles

DeepRobust: a Platform for Adversarial Attacks and Defenses

The Adapter-Bot: All-In-One Controllable Conversational Model

ACAT-G: An Interactive Learning Framework for Assisted Response Generation

RadarMath: An Intelligent Tutoring System for Math Education

i-Parser: Interactive Parser Development Kit for Natural Language Processing

SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models

Integrating Pre-trained Model into Rule-based Dialogue Management

Accelerating Data Discovery with an Ontology-driven Tool for an Enterprise-scale Data Lake Environment

Software for Agent-based Network Simulation and Visualization

ITRIX - an AI Enabled Solution for Orchestration of Recovery Instructions

The Active Sensing Testbed

EasyASR: A Distributed Machine Learning Platform for End-to-end Automatic Speech Recognition

CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge

IFDDS: An Anti-fraud Outbound Robot

TAILOR: Teaching with Active and Incremental Learning for Object Registration

MMKE: A Multi-Model Knowledge Extraction System from Unstructured Texts

Fashion Focus: Multi-modal Retrieval System for Video Commodity Localization in E-commerce