most citedSample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

cs.LG2026★ 2 cited

Sample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds

Gabor Paczolay, Matteo Papini, Alberto Maria Metelli +2

Several variance-reduced versions of REINFORCE based on importance sampling achieve an improved sample complexity to find an -stationary point, under an unrealistic…

cs.LG2026

Actor-Critic with Active Importance Sampling

Majid Molaei, Gabor Paczolay, Matteo Papini +2

This paper introduces the Active-Importance-Sampling Actor-Critic (AISAC) algorithm, an extension of the Actor-Critic framework for reducing variance in policy gradient estimation.…