Works (1)

Updated: April 5th, 2024 15:52

2023 journal article

Federated TD Learning Over Finite-Rate Erasure Channels: Linear Speedup Under Markovian Sampling


By: N. Dal Fabbro*, A. Mitra n & G. Pappas*

author keywords: Servers; Markov processes; Quantization (signal); Function approximation; Approximation algorithms; Reinforcement learning; Supervised learning; Machine learning; large-scale systems; communication networks
TL;DR: This work proposes and analyze QFedTD - a quantized federated temporal difference learning algorithm with linear function approximation that highlights the effect of quantization and erasures on the convergence rate and establishes a linear speedup w.r.t. the number of agents under Markovian sampling. (via Semantic Scholar)
Source: Web Of Science
Added: August 7, 2023

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