Statistical Learning

Non-parametric Inference Adaptive to Intrinsic Dimension CLeaR 2022 Non-Vacuous Generalisation Bounds for Shallow Neural Networks ICML 2022 Normalizing Flows for Knockoff-free Controlled Feature Selection NeurIPS 2022 Number Theory Meets Linguistics: Modelling Noun Pluralisation Across 1497 Languages Using 2-adic Metrics AACL 2022 Nystrom Regularization for Time Series Forecasting JMLR 2022 Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory ICML 2022 Off-Policy Risk Assessment for Markov Decision Processes AISTATS 2022 On A Mallows-type Model For (Ranked) Choices NeurIPS 2022 On characterizations of learnability with computable learners COLT 2022 One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation AISTATS 2022 On Gap-dependent Bounds for Offline Reinforcement Learning NeurIPS 2022 On Learning Mixture Models with Sparse Parameters AISTATS 2022 On Learning Mixture of Linear Regressions in the Non-Realizable Setting ICML 2022 On Linear Model with Markov Signal Priors AISTATS 2022 Online Control of the False Discovery Rate under "Decision Deadlines" AISTATS 2022 Online Learning and Pricing with Reusable Resources: Linear Bandits with Sub-Exponential Rewards ICML 2022 Online Nonnegative CP-dictionary Learning for Markovian Data JMLR 2022 Online PAC-Bayes Learning NeurIPS 2022 On Low-rank Trace Regression under General Sampling Distribution JMLR 2022 On Margins and Generalisation for Voting Classifiers NeurIPS 2022 On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data ACML 2022 On Some Fast And Robust Classifiers For High Dimension, Low Sample Size Data AISTATS 2022 On testability of the front-door model via Verma constraints UAI 2022 On the Assumptions of Synthetic Control Methods AISTATS 2022 On the Benefits of Large Learning Rates for Kernel Methods COLT 2022