Training on the Edge: The why and the how

13 February 2019

Papers citing "Training on the Edge: The why and the how"

7 / 7 papers shown

Title
Optimal Gradient Checkpoint Search for Arbitrary Computation Graphs Jianwei Feng Dong Huang 32 7 0 31 Jul 2018
Supporting Very Large Models using Automatic Dataflow Graph Partitioning Minjie Wang Chien-chin Huang Jinyang Li 91 155 0 24 Jul 2018
Moonshine: Distilling with Cheap Convolutions Elliot J. Crowley Gavia Gray Amos Storkey 57 121 0 07 Nov 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 427 2,945 0 15 Sep 2016
Memory-Efficient Backpropagation Through Time A. Gruslys Rémi Munos Ivo Danihelka Marc Lanctot Alex Graves 63 229 0 10 Jun 2016
Training Deep Nets with Sublinear Memory Cost Tianqi Chen Bing Xu Chiyuan Zhang Carlos Guestrin 103 1,171 0 21 Apr 2016
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems Tianqi Chen Mu Li Yutian Li Min Lin Naiyan Wang Minjie Wang Tianjun Xiao Bing Xu Chiyuan Zhang Zheng Zhang 196 2,248 0 03 Dec 2015