Learning Theory

Computation-information gap in high-dimensional clustering COLT 2024 Concentration and Moment Inequalities for General Functions of Independent Random Variables with Heavy Tails JMLR 2024 Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms IJCAI 2024 Confidence-aware Contrastive Learning for Selective Classification ICML 2024 Conformal Predictions under Markovian Data ICML 2024 Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them) ICML 2024 Consistency of Neural Causal Partial Identification NeurIPS 2024 Consistent Adversarially Robust Linear Classification: Non-Parametric Setting ICML 2024 CONTESTS: a Framework for Consistency Testing of Span Probabilities in Language Models EMNLP 2024 Continuous Prediction with Experts' Advice JMLR 2024 Contracting with a Learning Agent NeurIPS 2024 Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound NeurIPS 2024 Convergence Behavior of an Adversarial Weak Supervision Method UAI 2024 Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time ICML 2024 Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification NeurIPS 2024 Corruption-Robust Lipschitz Contextual Search ALT 2024 Credal Learning Theory NeurIPS 2024 CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption ALT 2024 Criterion Collapse and Loss Distribution Control ICML 2024 Critical Gap Between Generalization Error and Empirical Error in Active Learning WACV 2024 Critical Learning Periods Emerge Even in Deep Linear Networks ICLR 2024 Cumulative Regret Analysis of the Piyavskii–Shubert Algorithm and Its Variants for Global Optimization AAAI 2024 DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph NeurIPS 2024 Data Debugging with Shapley Importance over Machine Learning Pipelines ICLR 2024 Data-Driven Online Model Selection With Regret Guarantees AISTATS 2024