AutoAssist: A Framework to Accelerate Training of Deep Neural Networks

AutoAssist: A Framework to Accelerate Training of Deep Neural Networks

8 May 2019

Inderjit S. Dhillon

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Papers citing "AutoAssist: A Framework to Accelerate Training of Deep Neural Networks"

11 / 11 papers shown

Title
fairseq: A Fast, Extensible Toolkit for Sequence Modeling Myle Ott Sergey Edunov Alexei Baevski Angela Fan Sam Gross Nathan Ng David Grangier Michael Auli VLM FaML 114 3,156 0 01 Apr 2019
ScreenerNet: Learning Self-Paced Curriculum for Deep Neural Networks Tae-Hoon Kim Jonghyun Choi 45 9 0 03 Jan 2018
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 126 1,456 0 14 Dec 2017
Asymptotic Bias of Stochastic Gradient Search V. Tadic Arnaud Doucet 60 59 0 30 Aug 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,920 0 25 Aug 2017
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples Haw-Shiuan Chang Erik Learned-Miller Andrew McCallum 86 354 0 24 Apr 2017
Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning Yulia Tsvetkov Manaal Faruqui Wang Ling B. MacWhinney Chris Dyer 85 90 0 12 May 2016
Online Batch Selection for Faster Training of Neural Networks I. Loshchilov Frank Hutter ODL 100 301 0 19 Nov 2015
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks Samy Bengio Oriol Vinyals Navdeep Jaitly Noam M. Shazeer 152 2,038 0 09 Jun 2015
Stochastic Optimization with Importance Sampling P. Zhao Tong Zhang 100 346 0 13 Jan 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 324 1,250 0 10 Sep 2013

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