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Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations

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Go for a Walk and Arrive at the Answer: Reasoning Over Knowledge Bases with Reinforcement Learning., , , , , , , and . AKBC@NIPS, OpenReview.net, (2017)Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models., , , , , , , , , and . CoRR, (2022)Disagreement-Based Combinatorial Pure Exploration: Sample Complexity Bounds and an Efficient Algorithm., and . COLT, volume 99 of Proceedings of Machine Learning Research, page 558-588. PMLR, (2019)Subspace learning from extremely compressed measurements., , and . ACSSC, page 311-315. IEEE, (2014)Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression., , , , and . CoRR, (2023)Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics., , , , and . ICLR, OpenReview.net, (2022)Understanding Contrastive Learning Requires Incorporating Inductive Biases., , , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 19250-19286. PMLR, (2022)Oracle-Efficient Pessimism: Offline Policy Optimization In Contextual Bandits., , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 766-774. PMLR, (2024)Rich-Observation Reinforcement Learning with Continuous Latent Dynamics., , , and . ICML, OpenReview.net, (2024)A Complete Characterization of Linear Estimators for Offline Policy Evaluation., , , and . J. Mach. Learn. Res., (2023)