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cs.LG2025
Discovering New Theorems via LLMs with In-Context Proof Learning in Lean
Kazumi Kasaura, Naoto Onda, Yuta Oriike +3
Large Language Models (LLMs) have demonstrated significant promise in formal theorem proving. In this study, we investigate the ability of LLMs to discover novel theorems and produ…
cs.LG2025
Lean Formalization of Generalization Error Bound by Rademacher Complexity and Dudley's Entropy Integral
Sho Sonoda, Kazumi Kasaura, Yuma Mizuno +2
Understanding and certifying the generalization performance of machine learning algorithms -- i.e. obtaining theoretical estimates of the test error from the training error -- is a…
cs.LG2024
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees
Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato +6
We study a primal-dual (PD) reinforcement learning (RL) algorithm for online constrained Markov decision processes (CMDPs). Despite its widespread practical use, the existing theor…