The ZipML Framework for Training Models with End-to-End Low Precision:
The Cans, the Cannots, and a Little Bit of Deep Learning

The ZipML Framework for Training Models with End-to-End Low Precision: The Cans, the Cannots, and a Little Bit of Deep Learning

16 November 2016

Dan Alistarh

Papers citing "The ZipML Framework for Training Models with End-to-End Low Precision: The Cans, the Cannots, and a Little Bit of Deep Learning"

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Title
How Low Can We Go: Trading Memory for Error in Low-Precision Training Chengrun Yang Ziyang Wu Jerry Chee Christopher De Sa Madeleine Udell 23 2 0 17 Jun 2021
On-Device Machine Learning: An Algorithms and Learning Theory Perspective Sauptik Dhar Junyao Guo Jiayi Liu S. Tripathi Unmesh Kurup Mohak Shah 33 141 0 02 Nov 2019
CodedPrivateML: A Fast and Privacy-Preserving Framework for Distributed Machine Learning Jinhyun So Başak Güler A. Avestimehr FedML 30 114 0 02 Feb 2019
Gradient Sparsification for Communication-Efficient Distributed Optimization Jianqiao Wangni Jialei Wang Ji Liu Tong Zhang 15 522 0 26 Oct 2017