Suyog Gupta

22 papers A* 5A 1Journal 12Unranked 4
YearRankTypeTitle / Venue / Authors
2022 — conf
Searching for Efficient Neural Architectures for On-Device ML on Edge TPUs.
CVPR Workshops
Berkin Akin, Suyog Gupta, Yun Long, Anton Spiridonov, Zhuo Wang, Marie White, Hao Xu, Ping Zhou, Yanqi Zhou
2022 J jnl
Searching for Efficient Neural Architectures for On-Device ML on Edge TPUs.
CoRR
Berkin Akin, Suyog Gupta, Yun Long, Anton Spiridonov, Zhuo Wang, Marie White, Hao Xu, Ping Zhou, Yanqi Zhou
2021 J jnl
A critical review on water quality index tool: Genesis, evolution and future directions.
Ecol. Informatics
Suyog Gupta, Sunil Kumar Gupta
2021 — conf
Discovering Multi-Hardware Mobile Models via Architecture Search.
CVPR Workshops
Grace Chu, Okan Arikan, Gabriel Bender, Weijun Wang, Achille Brighton, Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard
2021 A* conf
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators.
CVPR
Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Yongzhe Wang, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen
2020 J jnl
Accelerator-aware Neural Network Design using AutoML.
CoRR
Suyog Gupta, Berkin Akin
2020 J jnl
Discovering Multi-Hardware Mobile Models via Architecture Search.
CoRR
Grace Chu, Okan Arikan, Gabriel Bender, Weijun Wang, Achille Brighton, Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard
2020 J jnl
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators.
CoRR
Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen
2019 J jnl
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling.
CoRR
Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia Xu Chen, Ye Jia, Anjuli Kannan, Tara N. 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 F. Foster, John Richardson, Klaus Macherey, Antoine Bruguier, Heiga Zen, Colin Raffel, Shankar Kumar, Kanishka Rao, David Rybach, Matthew Murray, Vijayaditya Peddinti, Maxim Krikun, Michiel Bacchiani, Thomas B. Jablin, Robert 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
2018 A conf
Compression of End-to-End Models.
INTERSPEECH
Ruoming Pang, Tara N. Sainath, Rohit Prabhavalkar, Suyog Gupta, Yonghui Wu, Shuyuan Zhang, Chung-Cheng Chiu
2018 — conf
To Prune, or Not to Prune: Exploring the Efficacy of Pruning for Model Compression.
ICLR (Workshop)
Michael Zhu, Suyog Gupta
2017 J jnl
Guest Editors' Introduction: Hardware and Algorithms for On-Chip Learning.
ACM J. Emerg. Technol. Comput. Syst.
Yu Cao, Xin Li, TaeMin Kim, Suyog Gupta
2017 A* conf
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study.
IJCAI
Suyog Gupta, Wei Zhang, Fei Wang
2017 J jnl
To prune, or not to prune: exploring the efficacy of pruning for model compression.
CoRR
Michael Zhu, Suyog Gupta
2016 — conf
Approximate computing: Challenges and opportunities.
ICRC
Ankur Agrawal, Jungwook Choi, Kailash Gopalakrishnan, Suyog Gupta, Ravi Nair, Jinwook Oh, Daniel A. Prener, Sunil Shukla, Vijayalakshmi Srinivasan, Zehra Sura
2016 A* conf
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study.
ICDM
Suyog Gupta, Wei Zhang, Fei Wang
2016 A* conf
Staleness-Aware Async-SGD for Distributed Deep Learning.
IJCAI
Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu
2015 A* conf
Deep Learning with Limited Numerical Precision.
ICML
Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan
2015 J jnl
Deep Learning with Limited Numerical Precision.
CoRR
Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan
2015 J jnl
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning.
CoRR
Suyog Gupta, Wei Zhang, Josh Milthorpe
2015 J jnl
Staleness-aware Async-SGD for Distributed Deep Learning.
CoRR
Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu
2014 J jnl
Learning Machines Implemented on Non-Deterministic Hardware.
CoRR
Suyog Gupta, Vikas Sindhwani, Kailash Gopalakrishnan