ICML

Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction

ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction

Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries

GC-Flow: A Graph-Based Flow Network for Effective Clustering

Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data

A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening

PromptBoosting: Black-Box Text Classification with Ten Forward Passes

Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models

Change is Hard: A Closer Look at Subpopulation Shift

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework

Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity

Differentiable Top-k Classification Learning

Entropic Causal Inference: Graph Identifiability

Selective Regression under Fairness Criteria

Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets

Prompting Decision Transformer for Few-shot Policy Generalization

CONTENTVEC: An Improved Self-Supervised Speech Representation by Disentangling Speakers

Data-Efficient Double-Win Lottery Tickets from Robust Pre-training

On Convergence of Gradient Descent Ascent: A Tight Local Analysis

Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision

Model Fusion with Kullback–Leibler Divergence

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

Curvature-corrected learning dynamics in deep neural networks

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

Linear Mode Connectivity and The Lottery Ticket Hypothesis

Two Simple Ways to Learn Individual Fairness Metrics from Data

Do GANs always have Nash equilibria?

Causal structure discovery from distributions arising from mixtures of DAGs

Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions

Neural Network Control Policy Verification with Persistent Adversarial Perturbations

Fair Selective Classification Via Sufficiency

AGENT: A Benchmark for Core Psychological Reasoning

Global Prosody Style Transfer Without Text Transcriptions

Auto-NBA: Efficient and Effective Search Over The Joint Space of Networks, Bitwidths, and Accelerators

Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?

Outlier-Robust Optimal Transport

Adversarial Option-Aware Hierarchical Imitation Learning

Bio-Inspired Hashing for Unsupervised Similarity Search