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GSPMD: General and Scalable Parallelization for ML Computation Graphs


May 10, 2021
Yuanzhong Xu, HyoukJoong Lee, Dehao Chen, Blake Hechtman, Yanping Huang, Rahul Joshi, Maxim Krikun, Dmitry Lepikhin, Andy Ly, Marcello Maggioni, Ruoming Pang, Noam Shazeer, Shibo Wang, Tao Wang, Yonghui Wu, Zhifeng Chen


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Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout


Oct 14, 2020
Zhao Chen, Jiquan Ngiam, Yanping Huang, Thang Luong, Henrik Kretzschmar, Yuning Chai, Dragomir Anguelov

* Conference on Neural Information Processing Systems (NeurIPS) 2020 

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GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding


Jun 30, 2020
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, Zhifeng Chen


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Do CNNs Encode Data Augmentations?


Feb 29, 2020
Eddie Yan, Yanping Huang


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Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling


Feb 21, 2019
Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia X. Chen, Ye Jia, Anjuli Kannan, Tara Sainath, Yuan Cao, Chung-Cheng Chiu, Yanzhang He, Jan Chorowski, Smit Hinsu, Stella Laurenzo, James Qin, Orhan Firat, Wolfgang Macherey, Suyog Gupta, Ankur Bapna, Shuyuan Zhang, Ruoming Pang, Ron J. Weiss, Rohit Prabhavalkar, Qiao Liang, Benoit Jacob, Bowen Liang, HyoukJoong Lee, Ciprian Chelba, Sébastien Jean, Bo Li, Melvin Johnson, Rohan Anil, Rajat Tibrewal, Xiaobing Liu, Akiko Eriguchi, Navdeep Jaitly, Naveen Ari, Colin Cherry, Parisa Haghani, Otavio Good, Youlong Cheng, Raziel Alvarez, Isaac Caswell, Wei-Ning Hsu, Zongheng Yang, Kuan-Chieh Wang, Ekaterina Gonina, Katrin Tomanek, Ben Vanik, Zelin Wu, Llion Jones, Mike Schuster, Yanping Huang, Dehao Chen, Kazuki Irie, George Foster, John Richardson, Klaus Macherey, Antoine Bruguier, Heiga Zen, Colin Raffel, Shankar Kumar, Kanishka Rao, David Rybach, Matthew Murray, Vijayaditya Peddinti, Maxim Krikun, Michiel A. U. Bacchiani, Thomas B. Jablin, Rob Suderman, Ian Williams, Benjamin Lee, Deepti Bhatia, Justin Carlson, Semih Yavuz, Yu Zhang, Ian McGraw, Max Galkin, Qi Ge, Golan Pundak, Chad Whipkey, Todd Wang, Uri Alon, Dmitry Lepikhin, Ye Tian, Sara Sabour, William Chan, Shubham Toshniwal, Baohua Liao, Michael Nirschl, Pat Rondon


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GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism


Dec 12, 2018
Yanping Huang, Yonglong Cheng, Dehao Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V. Le, Zhifeng Chen

* 10 pages. Work in progress. Copyright 2018 by the authors 

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Regularized Evolution for Image Classifier Architecture Search


Oct 26, 2018
Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V Le


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Learning Efficient Representations for Reinforcement Learning


Aug 28, 2015
Yanping Huang


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Partitioning Large Scale Deep Belief Networks Using Dropout


Aug 28, 2015
Yanping Huang, Sai Zhang

* arXiv admin note: text overlap with arXiv:1207.0580 by other authors 

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