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Post Reinforcement Learning Inference

arXiv:2302.08854v5 Announce Type: replace Abstract: We study estimation and inference using data collected by reinforcement learning (RL) algorithms. These algorithms adaptively experiment by interacting with individual units over multiple stages, updating their strategies based on past outcomes. Our goal is…

Optimal structure learning and conditional independence testing

arXiv:2507.05689v2 Announce Type: replace-cross Abstract: We establish a fundamental connection between optimal structure learning and optimal conditional independence testing by showing that the minimax optimal rate for structure learning problems is determined by the minimax rate for conditional independence testing…

Higher-arity PAC learning, VC dimension and packing lemma

arXiv:2510.02420v1 Announce Type: new Abstract: The aim of this note is to overview some of our work in Chernikov, Towsner’20 (arXiv:2010.00726) developing higher arity VC theory (VC$_n$ dimension), including a generalization of Haussler packing lemma, and an associated tame (slice-wise)…