Learning Theory

Auditing Local Explanations is Hard NeurIPS 2024 A Unified Characterization of Private Learnability via Graph Theory COLT 2024 A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits NeurIPS 2024 A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples ICML 2024 A Universal Class of Sharpness-Aware Minimization Algorithms ICML 2024 A Universal Growth Rate for Learning with Smooth Surrogate Losses NeurIPS 2024 Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics COLT 2024 Autoregressive Bandits AISTATS 2024 Average gradient outer product as a mechanism for deep neural collapse NeurIPS 2024 Averaging n-step Returns Reduces Variance in Reinforcement Learning ICML 2024 Bagging is an Optimal PAC Learner (Extended Abstract) IJCAI 2024 Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance ICML 2024 Balancing Context Length and Mixing Times for Reinforcement Learning at Scale NeurIPS 2024 Bandits with Concave Aggregated Reward IJCAI 2024 Bandits with Ranking Feedback NeurIPS 2024 Bayes-optimal learning of an extensive-width neural network from quadratically many samples NeurIPS 2024 BEACON: Benchmark for Comprehensive RNA Tasks and Language Models NeurIPS 2024 Benchmark Generation Framework With Customizable Distortions for Image Classifier Robustness WACV 2024 Benchmarking Structural Inference Methods for Interacting Dynamical Systems with Synthetic Data NeurIPS 2024 Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate ICLR 2024 Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data ICLR 2024 Benign Overfitting in Adversarial Training of Neural Networks ICML 2024 Benign overfitting in leaky ReLU networks with moderate input dimension NeurIPS 2024 Benign Overfitting in Two-Layer ReLU Convolutional Neural Networks for XOR Data ICML 2024 Best Arm Identification with Resource Constraints AISTATS 2024