mlsanityData to 7 Oct 2026

The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning

arXiv 2312.03120 ↗First posted 5 Dec 2023cs.LG cs.AI cs.DCcited by 0

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Abstract (arXiv)

With the advance of the powerful heterogeneous, parallel and distributed computing systems and ever increasing immense amount of data, machine learning has become an indispensable part of cutting-edge technology, scientific research and consumer products. In this study, we present a review of modern machine and deep learning. We provide a high-level overview for the latest advanced machine learning algorithms, applications, and frameworks. Our discussion encompasses parallel distributed learning, deep learning as well as federated learning. As a result, our work serves as an introductory text to the vast field of modern machine learning.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 74 of its 198 references that are in the map. First posted on arXiv 5 Dec 2023.

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74 of 198 references.

References · 74

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38 more
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