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Works (1)
Updated: April 5th, 2024 15:52
2023 journal article
Federated TD Learning Over Finite-Rate Erasure Channels: Linear Speedup Under Markovian Sampling
IEEE CONTROL SYSTEMS LETTERS, 7, 2461–2466.
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)
open access via ieeexplore.ieee.org (publisher PDF)
Source: Web Of Science
Added: August 7, 2023
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