Learning Theory

Open Ad Hoc Teamwork with Cooperative Game Theory ICML 2024 Open Problem: Anytime Convergence Rate of Gradient Descent COLT 2024 Open Problem: Can Local Regularization Learn All Multiclass Problems? COLT 2024 Open problem: Direct Sums in Learning Theory COLT 2024 Open Problem: Optimal Rates for Stochastic Decision-Theoretic Online Learning Under Differentially Privacy COLT 2024 Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning COLT 2024 Optimal Bump Functions for Shallow ReLU networks: Weight Decay, Depth Separation, Curse of Dimensionality JMLR 2024 Optimal Clustering with Bandit Feedback JMLR 2024 Optimal criterion for feature learning of two-layer linear neural network in high dimensional interpolation regime ICLR 2024 Optimal Design for Human Preference Elicitation NeurIPS 2024 Optimal estimation of Gaussian (poly)trees AISTATS 2024 Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks ICML 2024 Optimal Hypothesis Selection in (Almost) Linear Time NeurIPS 2024 Optimal Kernel Quantile Learning with Random Features ICML 2024 Optimal Learning Policies for Differential Privacy in Multi-armed Bandits JMLR 2024 Optimal Multi-Distribution Learning COLT 2024 Optimal Parallelization of Boosting NeurIPS 2024 Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms NeurIPS 2024 Optimal Sample Complexity for Average Reward Markov Decision Processes ICLR 2024 Optimal Sample Complexity of Contrastive Learning ICLR 2024 Optimal Top-Two Method for Best Arm Identification and Fluid Analysis NeurIPS 2024 Optimal Weighted Random Forests JMLR 2024 Optimistic Information Directed Sampling COLT 2024 Optimistic Rates for Learning from Label Proportions COLT 2024 Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes UAI 2024