Machine Learning

Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case

Linear Mode Connectivity and The Lottery Ticket Hypothesis

Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models

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

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

Two Simple Ways to Learn Individual Fairness Metrics from Data

Understanding Behavior of Clinical Models under Domain Shifts

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors

Wasserstein Style Transfer

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

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

Causal structure discovery from distributions arising from mixtures of DAGs

Ordering-based causal structure learning in the presence of latent variables

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning

Generating Adversarial Computer Programs using Optimized Obfuscations

High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation

Self-Progressing Robust Training

Neural Network Control Policy Verification with Persistent Adversarial Perturbations

Hidden Cost of Randomized Smoothing

PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics

Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning

Learning Task Decomposition with Ordered Memory Policy Network

Augmenting Policy Learning with Routines Discovered from a Single Demonstration

SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness

Individually Fair Gradient Boosting

Statistical inference for individual fairness

Black-box Explanation of Object Detectors via Saliency Maps

AGENT: A Benchmark for Core Psychological Reasoning

Adversarial Option-Aware Hierarchical Imitation Learning

Dense Associative Memory for Pattern Recognition

A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning

Can a Fruit Fly Learn Word Embeddings?

Adversarial T-shirt! Evading Person Detectors in A Physical World

Fast and efficient black-box testing for AI cybersecurity

Alleviating label switching with optimal transport

Learning Entropic Wasserstein Embeddings