Training Simplification and Model Simplification for Deep Learning: A
Minimal Effort Back Propagation Method

Training Simplification and Model Simplification for Deep Learning: A Minimal Effort Back Propagation Method

17 November 2017

Xuancheng Ren

Houfeng Wang

Papers citing "Training Simplification and Model Simplification for Deep Learning: A Minimal Effort Back Propagation Method"

5 / 5 papers shown

Title
Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format S. Shi Qiang-qiang Wang Xiaowen Chu 16 10 0 29 May 2020
Faster Neural Network Training with Approximate Tensor Operations Menachem Adelman Kfir Y. Levy Ido Hakimi M. Silberstein 31 26 0 21 May 2018
Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation Shuming Ma Xu Sun Wei Li Sujian Li Wenjie Li Xuancheng Ren 31 62 0 05 Mar 2018
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhehuai Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 718 6,750 0 26 Sep 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 218 7,929 0 17 Aug 2015