Learning Theory

Learning to Generalize Provably in Learning to Optimize AISTATS 2023 Learning to Generate Equitable Text in Dialogue from Biased Training Data ACL 2023 Learning Trajectories are Generalization Indicators NeurIPS 2023 Learning via Wasserstein-Based High Probability Generalisation Bounds NeurIPS 2023 Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB AISTATS 2023 Learning with Explanation Constraints NeurIPS 2023 Learn to Accumulate Evidence from All Training Samples: Theory and Practice ICML 2023 Leveraging Demonstrations to Improve Online Learning: Quality Matters ICML 2023 Leveraging the two-timescale regime to demonstrate convergence of neural networks NeurIPS 2023 Leveraging Unlabeled Data to Track Memorization ICLR 2023 Levin Tree Search with Context Models IJCAI 2023 Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization ALT 2023 Limitations on approximation by deep and shallow neural networks JMLR 2023 Limitless Stability for Graph Convolutional Networks ICLR 2023 Limits of Model Selection under Transfer Learning COLT 2023 Linear Reinforcement Learning with Ball Structure Action Space ALT 2023 List and Certificate Complexities in Replicable Learning NeurIPS 2023 List Online Classification COLT 2023 Literary Intertextual Semantic Change Detection: Application and Motivation for Evaluating Models on Small Corpora EMNLP 2023 Local Glivenko-Cantelli COLT 2023 Local Risk Bounds for Statistical Aggregation COLT 2023 Logarithmic regret in communicating MDPs: Leveraging known dynamics with bandits ACML 2023 Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games NeurIPS 2023 Lo-Hi: Practical ML Drug Discovery Benchmark NeurIPS 2023 LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization EACL 2023