Speeding Up Distributed Machine Learning Using Codes

DOI10.1109/TIT.2017.2736066zbMath1390.94879arXiv1512.02673MaRDI QIDQ4566725

Ramtin Pedarsani, Maximilian Lam, Kangwook Lee, Kannan Ramchandran, Dimitris S. Papailiopoulos

Publication date: 27 June 2018

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1512.02673

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Network design and communication in computer systems (68M10) Linear codes (general theory) (94B05)

Related Items (3)

MDS coding is better than replication for job completion times ⋮ Composite optimization with coupling constraints via dual proximal gradient method with applications to asynchronous networks ⋮ Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning

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