Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
Vienna
23-29 July 2022Edited by Luc De Raedt
Sponsored by
International Joint Conferences on Artifical Intelligence (IJCAI)
Published by
International Joint Conferences on Artificial Intelligence
Copyright © 2022 International Joint Conferences on Artificial Intelligence
All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher.
IJCAI Secretary-Treasurer: Kristian Kersting, Computer Science Department, Technical University of Darmstadt, Hochschulstraße 10, D-64289 Darmstadt, Germany
IJCAI Executive Director - IJCAI Executive Secretary Ms. Vesna Sabljakovic-Fritz, Vienna University of Technology, Institute of Discrete Mathematics and Geometry, E104 Wiedner Hauptstr. 8-10, A-1040 Vienna, Austria
ISBN (Online): 978-1-956792-00-3
Preface
Donwnload preface here.
Content
Main Track
Agent-based and Multi-agent Systems
Envy-Free and Pareto-Optimal Allocations for Agents with Asymmetric Random Valuations
Let’s Agree to Agree: Targeting Consensus for Incomplete Preferences through Majority Dynamics
Representation Matters: Characterisation and Impossibility Results for Interval Aggregation
Approximate Strategyproof Mechanisms for the Additively Separable Group Activity Selection Problem
The Dichotomous Affiliate Stable Matching Problem: Approval-Based Matching with Applicant-Employer Relations
Modelling the Dynamics of Multi-Agent Q-learning: The Stochastic Effects of Local Interaction and Incomplete Information
The Power of Media Agencies in Ad Auctions: Improving Utility through Coordinated Bidding
Modelling the Dynamics of Regret Minimization in Large Agent Populations: a Master Equation Approach
Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment
On the Complexity of Calculating Approval-Based Winners in Candidates-Embedded Metrics
Correlation-Based Algorithm for Team-Maxmin Equilibrium in Multiplayer Extensive-Form Games
AI Ethics, Trust, Fairness
How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations?
Model Stealing Defense against Exploiting Information Leak through the Interpretation of Deep Neural Nets
Counterfactual Interpolation Augmentation (CIA): A Unified Approach to Enhance Fairness and Explainability of DNN
Anti-Forgery: Towards a Stealthy and Robust DeepFake Disruption Attack via Adversarial Perceptual-aware Perturbations
Computer Vision
KPN-MFI: A Kernel Prediction Network with Multi-frame Interaction for Video Inverse Tone Mapping
Unsupervised Multi-Modal Medical Image Registration via Discriminator-Free Image-to-Image Translation
Robust Single Image Dehazing Based on Consistent and Contrast-Assisted Reconstruction
Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation
ICGNet: Integration Context-based Reverse-Contour Guidance Network for Polyp Segmentation
Lightweight Bimodal Network for Single-Image Super-Resolution via Symmetric CNN and Recursive Transformer
Learning Target-aware Representation for Visual Tracking via Informative Interactions
ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise
Perspective for Medical Image Segmentation
SatFormer: Saliency-Guided Abnormality-Aware Transformer for Retinal Disease Classification in Fundus Image
Online Hybrid Lightweight Representations Learning: Its Application to Visual Tracking
Robustifying Vision Transformer without Retraining from Scratch by Test-Time Class-Conditional Feature Alignment
What is Right for Me is Not Yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning
Representation Learning for Compressed Video Action Recognition via Attentive Cross-modal Interaction with Motion Enhancement
TCCNet: Temporally Consistent Context-Free Network for Semi-supervised Video Polyp Segmentation
Dynamic Group Transformer: A General Vision Transformer Backbone with Dynamic Group Attention
Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition
Long-Short Term Cross-Transformer in Compressed Domain for Few-Shot Video Classification
Improved Deep Unsupervised Hashing with Fine-grained Semantic Similarity Mining for Multi-Label Image Retrieval
Multilevel Hierarchical Network with Multiscale Sampling for Video Question Answering
Source-Adaptive Discriminative Kernels based Network for Remote Sensing Pansharpening
SimMC: Simple Masked Contrastive Learning of Skeleton Representations for Unsupervised Person Re-Identification
Harnessing Fourier Isovists and Geodesic Interaction for Long-Term Crowd Flow Prediction
Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information
I2CNet: An Intra- and Inter-Class Context Information Fusion Network for Blastocyst Segmentation
Uncertainty-Guided Pixel Contrastive Learning for Semi-Supervised Medical Image Segmentation
CARD: Semi-supervised Semantic Segmentation via Class-agnostic Relation based Denoising
Corner Affinity: A Robust Grouping Algorithm to Make Corner-guided Detector Great Again
Multi-scale Spatial Representation Learning via Recursive Hermite Polynomial Networks
A Decoder-free Transformer-like Architecture for High-efficiency Single Image Deraining
Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation
Boosting Multi-Label Image Classification with Complementary Parallel Self-Distillation
Weakening the Influence of Clothing: Universal Clothing Attribute Disentanglement for Person Re-Identification
Learning Implicit Body Representations from Double Diffusion Based Neural Radiance Fields
To Fold or Not to Fold: a Necessary and Sufficient Condition on Batch-Normalization Layers Folding
Region-level Contrastive and Consistency Learning for Semi-Supervised Semantic Segmentation
Improving Transferability of Adversarial Examples with Virtual Step and Auxiliary Gradients
A Probabilistic Code Balance Constraint with Compactness and Informativeness Enhancement for Deep Supervised Hashing
Rainy WCity: A Real Rainfall Dataset with Diverse Conditions for Semantic Driving Scene Understanding
Constraint Satisfaction and Optimization
Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies
Automated Program Analysis: Revisiting Precondition Inference through Constraint Acquisition
Threshold-free Pattern Mining Meets Multi-Objective Optimization: Application to Association Rules
Data Mining
Entity Alignment with Reliable Path Reasoning and Relation-aware Heterogeneous Graph Transformer
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting
Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting
When Transfer Learning Meets Cross-City Urban Flow Prediction: Spatio-Temporal Adaptation Matters
Modeling Precursors for Temporal Knowledge Graph Reasoning via Auto-encoder Structure
End-to-End Open-Set Semi-Supervised Node Classification with Out-of-Distribution Detection
CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning
Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs
TiRGN: Time-Guided Recurrent Graph Network with Local-Global Historical Patterns for Temporal Knowledge Graph Reasoning
Discrete Listwise Personalized Ranking for Fast Top-N Recommendation with Implicit Feedback
Reconciling Cognitive Modeling with Knowledge Forgetting: A Continuous Time-aware Neural Network Approach
Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features
Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion
Anomaly Detection by Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANs
MEIM: Multi-partition Embedding Interaction Beyond Block Term Format for Efficient and Expressive Link Prediction
HCFRec: Hash Collaborative Filtering via Normalized Flow with Structural Consensus for Efficient Recommendation
CTL-MTNet: A Novel CapsNet and Transfer Learning-Based Mixed Task Net for Single-Corpus and Cross-Corpus Speech Emotion Recognition
Understanding and Mitigating Data Contamination in Deep Anomaly Detection: A Kernel-based Approach
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Subgraph Neighboring Relations Infomax for Inductive Link Prediction on Knowledge Graphs
Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach
Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting
Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks
Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction
GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning
T-SMOTE: Temporal-oriented Synthetic Minority Oversampling Technique for Imbalanced Time Series Classification
Humans and AI
Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks
Forming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple Experts
Signed Neuron with Memory: Towards Simple, Accurate and High-Efficient ANN-SNN Conversion
Knowledge Representation and Reasoning
Annotated Sequent Calculi for Paraconsistent Reasoning and Their Relations to Logical Argumentation
Verification and Monitoring for First-Order LTL with Persistence-Preserving Quantification over Finite and Infinite Traces
Search Space Expansion for Efficient Incremental Inductive Logic Programming from Streamed Data
Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning
FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server
Machine Learning
Rethinking the Promotion Brought by Contrastive Learning to Semi-Supervised Node Classification
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images
Function-words Adaptively Enhanced Attention Networks for Few-Shot Inverse Relation Classification
Learning Unforgotten Domain-Invariant Representations for Online Unsupervised Domain Adaptation
DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data
A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks
Leveraging Class Abstraction for Commonsense Reinforcement Learning via Residual Policy Gradient Methods
Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks
SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities
Enhancing Unsupervised Domain Adaptation via Semantic Similarity Constraint for Medical Image Segmentation
Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training
On the Channel Pruning using Graph Convolution Network for Convolutional Neural Network Acceleration
Set Interdependence Transformer: Set-to-Sequence Neural Networks for Permutation Learning and Structure Prediction
Multi-policy Grounding and Ensemble Policy Learning for Transfer Learning with Dynamics Mismatch
Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration
Learning from Students: Online Contrastive Distillation Network for General Continual Learning
Cross-modal Representation Learning and Relation Reasoning for Bidirectional Adaptive Manipulation
Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization
JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning
Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors
Towards Robust Unsupervised Disentanglement of Sequential Data — A Case Study Using Music Audio
COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence
Composing Neural Learning and Symbolic Reasoning with an Application to Visual Discrimination
Certified Robustness via Randomized Smoothing over Multiplicative Parameters of Input Transformations
Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts
PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations
CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement Learning
Stochastic Coherence Over Attention Trajectory For Continuous Learning In Video Streams
Unsupervised Misaligned Infrared and Visible Image Fusion via Cross-Modality Image Generation and Registration
Modeling Spatio-temporal Neighbourhood for Personalized Point-of-interest Recommendation
Multi-Player Multi-Armed Bandits with Finite Shareable Resources Arms: Learning Algorithms & Applications
Automatically Gating Multi-Frequency Patterns through Rectified Continuous Bernoulli Units with Theoretical Principles
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Online ECG Emotion Recognition for Unknown Subjects via Hypergraph-Based Transfer Learning
EGCN: An Ensemble-based Learning Framework for Exploring Effective Skeleton-based Rehabilitation Exercise Assessment
Don’t Touch What Matters: Task-Aware Lipschitz Data Augmentation for Visual Reinforcement Learning
Het2Hom: Representation of Heterogeneous Attributes into Homogeneous Concept Spaces for Categorical-and-Numerical-Attribute Data Clustering
Learning Mixture of Neural Temporal Point Processes for Multi-dimensional Event Sequence Clustering
Multidisciplinary Topics and Applications
Subsequence-based Graph Routing Network for Capturing Multiple Risk Propagation Processes
3E-Solver: An Effortless, Easy-to-Update, and End-to-End Solver with Semi-Supervised Learning for Breaking Text-Based Captchas
A Universal PINNs Method for Solving Partial Differential Equations with a Point Source
A Polynomial-time Decentralised Algorithm for Coordinated Management of Multiple Intersections
Multi-Agent Reinforcement Learning for Traffic Signal Control through Universal Communication Method
Cumulative Stay-time Representation for Electronic Health Records in Medical Event Time Prediction
Self-Supervised Learning with Attention-based Latent Signal Augmentation for Sleep Staging with Limited Labeled Data
Transformer-based Objective-reinforced Generative Adversarial Network to Generate Desired Molecules
Towards Controlling the Transmission of Diseases: Continuous Exposure Discovery over Massive-Scale Moving Objects
Monolith to Microservices: Representing Application Software through Heterogeneous Graph Neural Network
Learn Continuously, Act Discretely: Hybrid Action-Space Reinforcement Learning For Optimal Execution
Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction
FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting
Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit
Local Differential Privacy Meets Computational Social Choice - Resilience under Voter Deletion
Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited
Exploring the Vulnerability of Deep Reinforcement Learning-based Emergency Control for Low Carbon Power Systems
Heterogeneous Interactive Snapshot Network for Review-Enhanced Stock Profiling and Recommendation
Bridging the Gap between Reality and Ideality of Entity Matching: A Revisting and Benchmark Re-Constrcution
TinyLight: Adaptive Traffic Signal Control on Devices with Extremely Limited Resources
Temporality Spatialization: A Scalable and Faithful Time-Travelling Visualization for Deep Classifier Training
Natural Language Processing
Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings
DictBERT: Dictionary Description Knowledge Enhanced Language Model Pre-training via Contrastive Learning
Global Inference with Explicit Syntactic and Discourse Structures for Dialogue-Level Relation Extraction
Inheriting the Wisdom of Predecessors: A Multiplex Cascade Framework for Unified Aspect-based Sentiment Analysis
Curriculum-Based Self-Training Makes Better Few-Shot Learners for Data-to-Text Generation
Taylor, Can You Hear Me Now? A Taylor-Unfolding Framework for Monaural Speech Enhancement
FastRE: Towards Fast Relation Extraction with Convolutional Encoder and Improved Cascade Binary Tagging Framework
Neutral Utterances are Also Causes: Enhancing Conversational Causal Emotion Entailment with Social Commonsense Knowledge
“My nose is running.” “Are you also coughing?”: Building A Medical Diagnosis Agent with Interpretable Inquiry Logics
Prompting to Distill: Boosting Data-Free Knowledge Distillation via Reinforced Prompt
Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation
Document-level Event Factuality Identification via Reinforced Multi-Granularity Hierarchical Attention Networks
A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model
MGAD: Learning Descriptional Representation Distilled from Distributional Semantics for Unseen Entities
Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval
Propose-and-Refine: A Two-Stage Set Prediction Network for Nested Named Entity Recognition
Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning
TaxoPrompt: A Prompt-based Generation Method with Taxonomic Context for Self-Supervised Taxonomy Expansion
Robust Interpretable Text Classification against Spurious Correlations Using AND-rules with Negation
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine Translation
Targeted Multimodal Sentiment Classification based on Coarse-to-Fine Grained Image-Target Matching
Stage-wise Stylistic Headline Generation: Style Generation and Summarized Content Insertion
EditSinger: Zero-Shot Text-Based Singing Voice Editing System with Diverse Prosody Modeling
“Think Before You Speak”: Improving Multi-Action Dialog Policy by Planning Single-Action Dialogs
Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph
Planning and Scheduling
An Online Learning Approach towards Far-sighted Emergency Relief Planning under Intentional Attacks in Conflict Areas
Robotics
Search
Completeness and Diversity in Depth-First Proof-Number Search with Applications to Retrosynthesis
Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables
Efficient Algorithms for Monotone Non-Submodular Maximization with Partition Matroid Constraint
HEA-D: A Hybrid Evolutionary Algorithm for Diversified Top-k Weight Clique Search Problem
Uncertainty in AI
Empirical Bayesian Approaches for Robust Constraint-based Causal Discovery under Insufficient Data
Robustness Guarantees for Credal Bayesian Networks via Constraint Relaxation over Probabilistic Circuits
Special Track on AI, the Arts and Creativity
Research Papers
Towards Creativity Characterization of Generative Models via Group-Based Subset Scanning
Threshold Designer Adaptation: Improved Adaptation for Designers in Co-creative Systems
Dataset Augmentation in Papyrology with Generative Models: A Study of Synthetic Ancient Greek Character Images
Special Track on AI for Good
Research Papers
A Murder and Protests, the Capitol Riot, and the Chauvin Trial: Estimating Disparate News Media Stance
Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net
Am I No Good? Towards Detecting Perceived Burdensomeness and Thwarted Belongingness from Suicide Notes
AI Facilitated Isolations? The Impact of Recommendation-based Influence Diffusion in Human Society
Crowd, Expert & AI: A Human-AI Interactive Approach Towards Natural Language Explanation Based COVID-19 Misinformation Detection
Creating Dynamic Checklists via Bayesian Case-Based Reasoning: Towards Decent Working Conditions for All
A Reliability-aware Distributed Framework to Schedule Residential Charging of Electric Vehicles
ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in Nigeria
AgriBERT: Knowledge-Infused Agricultural Language Models for Matching Food and Nutrition
CounterGeDi: A Controllable Approach to Generate Polite, Detoxified and Emotional Counterspeech
Scalable and Memory-Efficient Algorithms for Controlling Networked Epidemic Processes Using Multiplicative Weights Update Method
Revealing the Excitation Causality between Climate and Political Violence via a Neural Forward-Intensity Poisson Process
Forecasting the Number of Tenants At-Risk of Formal Eviction: A Machine Learning Approach to Inform Public Policy
Dynamic Structure Learning through Graph Neural Network for Forecasting Soil Moisture in Precision Agriculture
Projects
Sister Conferences Best Papers
Utilizing Treewidth for Quantitative Reasoning on Epistemic Logic Programs (Extended Abstract)
Capturing Homomorphism-Closed Decidable Queries with Existential Rules (Extended Abstract)
Measuring Data Leakage in Machine-Learning Models with Fisher Information (Extended Abstract)
Allocating Opportunities in a Dynamic Model of Intergenerational Mobility (Extended Abstract)
Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent (Extended Abstract)
Open Data Science to Fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge (Extended Abstract)
Detect, Understand, Act: A Neuro-Symbolic Hierarchical Reinforcement Learning Framework (Extended Abstract)
Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness (Extended Abstract)
Logic Rules Meet Deep Learning: A Novel Approach for Ship Type Classification (Extended Abstract)
Asymmetric Hybrids: Dialogues for Computational Concept Combination (Extended Abstract)
Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach (Extended Abstract)
Black-box Audit of YouTube's Video Recommendation: Investigation of Misinformation Filter Bubble Dynamics (Extended Abstract)
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies (Extended Abstract)
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication (Extended Abstract)
Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space (Extended Abstract)
Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval (Extended Abstract)
Survey Track
Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks
Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code
On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges
Journal Track
On the First-Order Rewritability of Ontology-Mediated Queries in Linear Temporal Logic (Extended Abstract)
Overlapping Communities and Roles in Networks with Node Attributes: Probabilistic Graphical Modeling, Bayesian Formulation and Variational Inference (Extended Abstract)
On Quantifying Literals in Boolean Logic and its Applications to Explainable AI (Extended Abstract)
Situation Calculus for Controller Synthesis in Manufacturing Systems with First-Order State Representation (Extended Abstract)
Experimental Comparison and Survey of Twelve Time Series Anomaly Detection Algorithms (Extended Abstract)
Dimensional Inconsistency Measures and Postulates in Spatio-Temporal Databases (Extended Abstract)
Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency Maps (Extended Abstract)
Learning Realistic Patterns from Visually Unrealistic Stimuli: Generalization and Data Anonymization (Extended Abstract)
Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks (Extended Abstract)*
Ethics and Governance of Artificial Intelligence: A Survey of Machine Learning Researchers (Extended Abstract)
Early Career
Irrational, but Adaptive and Goal Oriented: Humans Interacting with Autonomous Agents
Doctoral Consortium
Towards New Optimized Artificial Immune Recognition Systems under the Belief Function Theory
Decentralized Autonomous Organizations and Multi-agent Systems for Artificial Intelligence Applications and Data Analysis
Early Diagnosis of Lyme Disease by Recognizing Erythema Migrans Skin Lesion from Images Utilizing Deep Learning Techniques
Transferability and Stability of Learning with Limited Labelled Data in Multilingual Text Document Classification
Data-Efficient Algorithms and Neural Natural Language Processing: Applications in the Healthcare Domain
A Model-Oriented Approach for Lifting Symmetry-Breaking Constraints in Answer Set Programming
Adaptive Artificial Intelligence Scheduling Methods for Large-Scale, Stochastic, Industrial Applications
Demo Track
Interactive Reinforcement Learning for Symbolic Regression from Multi-Format Human-Preference Feedbacks
A Speech-driven Sign Language Avatar Animation System for Hearing Impaired Applications
PillGood: Automated and Interactive Pill Dispenser Using Facial Recognition for Safe and Personalized Medication
Sign-to-Speech Model for Sign Language Understanding: A Case Study of Nigerian Sign Language
The Good, the Bad, and the Explainer: A Tool for Contrastive Explanations of Text Classifiers
ACTA 2.0: A Modular Architecture for Multi-Layer Argumentative Analysis of Clinical Trials
Fine-tuning Deep Neural Networks by Interactively Refining the 2D Latent Space of Ambiguous Images