A Reinforcement Learning-Based Approach to Graph Discovery in D2D-Enabled Federated Learning

Satyavrat Wagle, Anindya Bijoy Das, David J. Love, Christopher G. Brinton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Augmenting federated learning (FL) with direct device-to-device (D2D) communications can help improve conver-gence speed and reduce model bias through rapid local information exchange. However, data privacy concerns, device trust issues, and unreliable wireless channels each pose challenges to determining an effective yet resource efficient D2D structure. In this paper, we develop a decentralized reinforcement learning (RL) methodology for D2D graph discovery that promotes communication of non-sensitive yet impactful data-points over trusted yet reliable links. Each device functions as an RL agent, training a policy to predict the impact of incoming links. Local (device-level) and global rewards are coupled through message passing within and between device clusters. Numerical experiments confirm the advantages offered by our method in terms of convergence speed and straggler resilience across several datasets and FL schemes.

Original languageEnglish (US)
Title of host publicationGLOBECOM 2023 - 2023 IEEE Global Communications Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages225-230
Number of pages6
ISBN (Electronic)9798350310900
DOIs
StatePublished - 2023
Externally publishedYes
Event2023 IEEE Global Communications Conference, GLOBECOM 2023 - Kuala Lumpur, Malaysia
Duration: Dec 4 2023Dec 8 2023

Publication series

NameProceedings - IEEE Global Communications Conference, GLOBECOM
ISSN (Print)2334-0983
ISSN (Electronic)2576-6813

Conference

Conference2023 IEEE Global Communications Conference, GLOBECOM 2023
Country/TerritoryMalaysia
CityKuala Lumpur
Period12/4/2312/8/23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing

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