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Robust Semi-Decentralized Federated Learning via Collaborative Relaying
Michal Yemini
, Rajarshi Saha
, Emre Ozfatura
, Deniz Gunduz
,
Andrea J. Goldsmith
Electrical and Computer Engineering
NextG
School of Engineering & Applied Science
Research output
:
Contribution to journal
›
Article
›
peer-review
5
Scopus citations
Overview
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Keyphrases
Parameter Server
100%
Semi-decentralized Federated Learning
100%
Collaborative Relaying
100%
Local Averaging
33%
Convergence Rate
16%
Numerical Evaluation
16%
Blockage
16%
Minimal Variance
16%
Learning Framework
16%
Data Distribution
16%
Local Update
16%
Local Data
16%
Restricted Connectivity
16%
Intermittently Connected Networks
16%
Intermittent Connectivity
16%
Constant Connectivity
16%
CIFAR10 Dataset
16%
Federated Learning System
16%
Communication Round
16%
Millimeter Wave Channel
16%
Federated Averaging
16%
Federated Edge Learning
16%
Generalization Gap
16%
Intermittent Communication
16%
Client Relay
16%
Communication Outage
16%
Computer Science
Federated Learning
100%
Parameter Server
100%
Learning Framework
33%
Convergence Rate
16%
Connected Network
16%
Data Distribution
16%
Weighted Average
16%