Hugging Face Trending Papers June 4, 2026

Fast and Robust Convergence Rate for TD(0) with Linear Function Approximation, Universal Learning Steps and I.I.D. Samples

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In this paper, we study the finite-time behavior of the TD(0) temporal-difference method with linear function approximation (LFA). We consider on-policy independent and identically distributed (i.

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arXiv Machine Learning

Jun 5

Fast and Robust Convergence Rate for TD(0) with Linear Function Approximation, Universal Learning Steps and I.I.D. Samples

arXiv:2606. 05967v1 Announce Type: cross Abstract: In this paper, we study the finite-time behavior of the TD(0) temporal-difference method with linear function approximation (LFA).

By Ziad Kobeissi (L2S), \'Elo\"ise Berthier (U2IS)

arXiv Machine Learning

Jun 9

A Robust $\widetilde{\mathcal{O}}(1/\sqrt{T})$ Rate for Unprojected TD Learning with Linear Function Approximation

arXiv:2506. 01052v3 Announce Type: replace Abstract: We investigate the finite-time convergence properties of Temporal Difference (TD) learning with linear function approximation, a cornerstone of reinforcement learning.

By Wei-Cheng Lee, Francesco Orabona

reinforcement-learning

arXiv Machine Learning

Sep 15

Steady-State Convergence of Stochastic Approximation

arXiv:2609.14922v1 Announce Type: cross Abstract: For constant-stepsize stochastic approximation (SA), the iterates converge in distribution to a stationary law that depends on the stepsize $\alpha.$...

By Yixuan Zhang, Qiaomin Xie

reinforcement-learning safety

arXiv Statistics ML

3d ago

Sharp Statistical Rates for Asynchronous TD Learning with Markovian Data

arXiv:2609.38880v1 Announce Type: new Abstract: We study the last iterate of standard tabular temporal-difference (TD) learning from a single trajectory of a finite Markov reward process. For discoun...

By Yang Peng

arXiv Machine Learning

4d ago

Markovian Nonconvex ADMM for Reinforcement Learning: Bellman-Resolvent Stability Beyond Smooth Blocks

arXiv:2609.36859v1 Announce Type: new Abstract: We identify and study a structural mechanism for Markovian nonconvex ADMM in reinforcement learning. Using finite discounted MDPs as a canonical provin...

By Zhaojun Peng

reinforcement-learning safety

arXiv Machine Learning

Jun 25

A Single Stepsize Suffices for Unprojected Linear TD(0): Simultaneous Robust and Fast Rates via Polyak--Ruppert Averaging

arXiv:2606. 24981v1 Announce Type: new Abstract: We study linear TD(0) under Markovian sampling, where data are generated along a single trajectory.

By Wei-Cheng Lee, Francesco Orabona

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Fast and Robust Convergence Rate for TD(0) with Linear Function Approximation, Universal Learning Steps and I.I.D. Samples

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