Collaborative Distributed Machine Learning

David Jin

doi:10.1145/3704807

Collaborative Distributed Machine Learning

2024-12-24

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DOI：10.1145/3704807

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Abstract

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Various collaborative distributed machine learning (CDML) systems, including federated learning systems and swarm learning systems, with different key traits were developed to leverage resources for the development and use of machine learning models in a confidentiality-preserving way. To meet use case requirements, suitable CDML systems need to be selected. However, comparison between CDML systems to assess their suitability for use cases is often difficult. To support comparison of CDML systems and introduce scientific and practical audiences to the principal functioning and key traits of CDML systems, this work presents a CDML system conceptualization and CDML archetypes.

Keywords:

Collaborative distributed machine learning (CDML)

privacy-enhancing technologies (PETs)

assisted learning

federated learning (FL)

split learning

swarm learning

multi-agent systems (MAS)

Collaborative Distributed Machine Learning

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