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Large-Scale Learning with Less RAM via Randomization

Large-Scale Learning with Less RAM via Randomization

International Conference on Machine Learning (ICML), 2013
19 March 2013
Daniel Golovin
D. Sculley
H. B. McMahan
Michael Young
ArXiv (abs)PDFHTML

Papers citing "Large-Scale Learning with Less RAM via Randomization"

5 / 5 papers shown
Incentives for Federated Learning: a Hypothesis Elicitation Approach
Incentives for Federated Learning: a Hypothesis Elicitation Approach
Yang Liu
Jiaheng Wei
FedML
159
24
0
21 Jul 2020
On-Device Machine Learning: An Algorithms and Learning Theory
  Perspective
On-Device Machine Learning: An Algorithms and Learning Theory Perspective
Sauptik Dhar
Junyao Guo
Jiayi Liu
S. Tripathi
Unmesh Kurup
Mohak Shah
460
173
0
02 Nov 2019
Sketching Linear Classifiers over Data Streams
Sketching Linear Classifiers over Data Streams
Kai Sheng Tai
Willie Neiswanger
Peter Bailis
Gregory Valiant
135
1
0
07 Nov 2017
Stochastic, Distributed and Federated Optimization for Machine Learning
Stochastic, Distributed and Federated Optimization for Machine Learning
Jakub Konecný
FedML
195
38
0
04 Jul 2017
Federated Learning: Strategies for Improving Communication Efficiency
Federated Learning: Strategies for Improving Communication Efficiency
Jakub Konecný
H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
FedML
666
5,185
0
18 Oct 2016
1
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