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cs.LG2024★ 3 cited
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
Arman Adibi, Nicolo Dal Fabbro, Luca Schenato +5
Motivated by applications in large-scale and multi-agent reinforcement learning, we study the non-asymptotic performance of stochastic approximation (SA) schemes with delayed updat…
cs.AI2024
DASA: Delay-Adaptive Multi-Agent Stochastic Approximation
Nicolò Dal Fabbro, Arman Adibi, H. Vincent Poor +3
We consider a setting in which agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server. We assume tha…