Learning Theory

PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency AISTATS 2022 PAC Mode Estimation using PPR Martingale Confidence Sequences AISTATS 2022 PAC Prediction Sets for Meta-Learning NeurIPS 2022 PAC Prediction Sets Under Covariate Shift ICLR 2022 PAC Top-k Identification under SST in Limited Rounds AISTATS 2022 Parameter-free Regret in High Probability with Heavy Tails NeurIPS 2022 Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference NeurIPS 2022 Parsimonious Learning-Augmented Caching ICML 2022 PDE-Based Optimal Strategy for Unconstrained Online Learning ICML 2022 PDEBench: An Extensive Benchmark for Scientific Machine Learning NeurIPS 2022 Pessimism for Offline Linear Contextual Bandits using ℓ_p Confidence Sets NeurIPS 2022 Phase transitions in when feedback is useful NeurIPS 2022 Phenomenology of Double Descent in Finite-Width Neural Networks ICLR 2022 Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation NeurIPS 2022 Plurality Veto: A Simple Voting Rule Achieving Optimal Metric Distortion IJCAI 2022 PMAL: Open Set Recognition via Robust Prototype Mining AAAI 2022 Policy Optimization for Stochastic Shortest Path COLT 2022 Popular decision tree algorithms are provably noise tolerant ICML 2022 Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression NeurIPS 2022 Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm NeurIPS 2022 Predicting Difficulty and Discrimination of Natural Language Questions ACL 2022 Predicting Fine-Tuning Performance with Probing EMNLP 2022 Principal Components Bias in Over-parameterized Linear Models, and its Manifestation in Deep Neural Networks JMLR 2022 Provable Domain Generalization via Invariant-Feature Subspace Recovery ICML 2022 Provable General Function Class Representation Learning in Multitask Bandits and MDP NeurIPS 2022