PulseAugur
EN
LIVE 07:18:55

New Central Limit Theorem for TD Learning Published on arXiv

By PulseAugur Editorial · [1 sources] ·

This paper, submitted to arXiv, presents a non-asymptotic central limit theorem for vector-valued martingale differences using Stein's method. The authors extend this to functions of Markov Chains and demonstrate its application to Temporal Difference (TD) learning with averaging, establishing a non-asymptotic central limit theorem for this specific learning method. AI

IMPACT Provides a theoretical framework for understanding the convergence properties of Temporal Difference learning algorithms.

RANK_REASON Academic paper published on arXiv detailing a new theoretical result with an application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Central Limit Theorem for TD Learning Published on arXiv

How we ranked this

Signal score
23 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
Academic paper published on arXiv detailing a new theoretical result with an application. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · R. Srikant ·

    Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning

    arXiv:2401.15719v5 Announce Type: replace-cross Abstract: We prove a non-asymptotic central limit theorem for vector-valued martingale differences using Stein's method, and use Poisson's equation to extend the result to functions of Markov Chains. We then show that these results …

RELATED ENTITIES

RELATED TOPICS