Is this your profile?
Claim your Citation Index profile in order to display more information about you and gain access to Libraries services. Just create or connect your ORCID iD.
Create or connect your ORCID iD
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)
ieeexplore.ieee.org (publisher PDF)
Source: Web Of Science
Added: August 7, 2023
Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.
Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
