Web: http://arxiv.org/abs/2108.08842

Jan. 31, 2022, 2:11 a.m. | Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher

cs.LG updates on arXiv.org arxiv.org

Distributed Mean Estimation (DME) is a central building block in federated
learning, where clients send local gradients to a parameter server for
averaging and updating the model. Due to communication constraints, clients
often use lossy compression techniques to compress the gradients, resulting in
estimation inaccuracies.

DME is more challenging when clients have diverse network conditions, such as
constrained communication budgets and packet losses. In such settings, DME
techniques often incur a significant increase in the estimation error leading
to degraded …

arxiv communication distributed federated learning learning

More from arxiv.org / cs.LG updates on arXiv.org

Senior Data Analyst

@ Fanatics Inc | Remote - New York

Data Engineer - Search

@ Cytora | United Kingdom - Remote

Product Manager, Technical - Data Infrastructure and Streaming

@ Nubank | Berlin

Postdoctoral Fellow: ML for autonomous materials discovery

@ Lawrence Berkeley National Lab | Berkeley, CA

Principal Data Scientist

@ Zuora | Remote

Data Engineer

@ Veeva Systems | Pennsylvania - Fort Washington