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HCSFL

Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge

Install / Use

/learn @COPS-IITBHU/HCSFL
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

HCSFL

Implementation of Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge

  • It is a decentralised learning framework that enables privacy preserving training of ML models for heterogeneous clients on practical networks.
  • Wrote unit tests for various components of Envisedge - a deployment library for recommendation engines with Edge Computing. github
View on GitHub
GitHub Stars42
CategoryEducation
Updated18d ago
Forks10

Languages

Python

Security Score

75/100

Audited on Mar 14, 2026

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