A
Ashwinee Panda
Researcher at University of California, Berkeley
Publications - 3
Citations - 184
Ashwinee Panda is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Sketch & Bottleneck. The author has an hindex of 2, co-authored 3 publications receiving 65 citations.
Papers
More filters
Proceedings Article
FetchSGD: Communication-Efficient Federated Learning with Sketching.
Daniel Rothchild,Ashwinee Panda,Enayat Ullah,Nikita Ivkin,Ion Stoica,Vladimir Braverman,Joseph E. Gonzalez,Raman Arora +7 more
TL;DR: This paper introduces a novel algorithm, called FetchSGD, which compresses model updates using a Count Sketch, and then takes advantage of the mergeability of sketches to combine model updates from many workers.
Posted Content
FetchSGD: Communication-Efficient Federated Learning with Sketching
Daniel Rothchild,Ashwinee Panda,Enayat Ullah,Nikita Ivkin,Ion Stoica,Vladimir Braverman,Joseph E. Gonzalez,Raman Arora +7 more
TL;DR: FetchSGD as discussed by the authors compresses model updates using a count sketch, and then takes advantage of the mergeability of sketches to combine model updates from many workers to overcome the communication bottleneck and convergence issues.
Proceedings Article
Communication-Efficient Federated Learning with Sketching
Daniel Rothchild,Ashwinee Panda,Enayat Ullah,Nikita Ivkin,Vladimir Braverman,Joseph E. Gonzalez,Ion Stoica,Raman Arora +7 more
TL;DR: This paper introduces a novel algorithm, called FedSketchedSGD, which compresses model updates using a Count Sketch, and then takes advantage of the mergeability of sketches to combine model updates from many workers.