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Suyog Gupta
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2020 – today
- 2022
- [c10]Berkin Akin, Suyog Gupta, Yun Long, Anton Spiridonov, Zhuo Wang, Marie White, Hao Xu, Ping Zhou
, Yanqi Zhou:
Searching for Efficient Neural Architectures for On-Device ML on Edge TPUs. CVPR Workshops 2022: 2666-2675 - [i10]Berkin Akin, Suyog Gupta, Yun Long, Anton Spiridonov, Zhuo Wang, Marie White, Hao Xu, Ping Zhou, Yanqi Zhou:
Searching for Efficient Neural Architectures for On-Device ML on Edge TPUs. CoRR abs/2204.14007 (2022) - 2021
- [j2]Suyog Gupta
A critical review on water quality index tool: Genesis, evolution and future directions. Ecol. Informatics 63: 101299 (2021) - [c9]Grace Chu, Okan Arikan, Gabriel Bender, Weijun Wang, Achille Brighton, Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard:
Discovering Multi-Hardware Mobile Models via Architecture Search. CVPR Workshops 2021: 3022-3031 - [c8]Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Yongzhe Wang, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen:
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. CVPR 2021: 3825-3834 - 2020
- [i9]Suyog Gupta, Berkin Akin:
Accelerator-aware Neural Network Design using AutoML. CoRR abs/2003.02838 (2020) - [i8]Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen:
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. CoRR abs/2004.14525 (2020) - [i7]Grace Chu, Okan Arikan, Gabriel Bender, Weijun Wang, Achille Brighton, Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard:
Discovering Multi-Hardware Mobile Models via Architecture Search. CoRR abs/2008.08178 (2020)
2010 – 2019
- 2019
- [i6]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:
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling. CoRR abs/1902.08295 (2019) - 2018
- [c7]Michael Zhu, Suyog Gupta:
To Prune, or Not to Prune: Exploring the Efficacy of Pruning for Model Compression. ICLR (Workshop) 2018 - [c6]Ruoming Pang, Tara N. Sainath, Rohit Prabhavalkar
Compression of End-to-End Models. INTERSPEECH 2018: 27-31 - 2017
- [j1]Yu Cao
Guest Editors' Introduction: Hardware and Algorithms for On-Chip Learning. ACM J. Emerg. Technol. Comput. Syst. 13(3): 30:1-30:3 (2017) - [c5]Suyog Gupta, Wei Zhang, Fei Wang:
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study. IJCAI 2017: 4854-4858 - [i5]Michael Zhu, Suyog Gupta:
To prune, or not to prune: exploring the efficacy of pruning for model compression. CoRR abs/1710.01878 (2017) - 2016
- [c4]Suyog Gupta, Wei Zhang, Fei Wang:
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study. ICDM 2016: 171-180 - [c3]Ankur Agrawal, Jungwook Choi, Kailash Gopalakrishnan, Suyog Gupta, Ravi Nair, Jinwook Oh, Daniel A. Prener, Sunil Shukla, Vijayalakshmi Srinivasan, Zehra Sura:
Approximate computing: Challenges and opportunities. ICRC 2016: 1-8 - [c2]Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu:
Staleness-Aware Async-SGD for Distributed Deep Learning. IJCAI 2016: 2350-2356 - 2015
- [c1]Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan:
Deep Learning with Limited Numerical Precision. ICML 2015: 1737-1746 - [i4]Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan:
Deep Learning with Limited Numerical Precision. CoRR abs/1502.02551 (2015) - [i3]Suyog Gupta, Wei Zhang, Josh Milthorpe:
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning. CoRR abs/1509.04210 (2015) - [i2]Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu:
Staleness-aware Async-SGD for Distributed Deep Learning. CoRR abs/1511.05950 (2015) - 2014
- [i1]Suyog Gupta, Vikas Sindhwani, Kailash Gopalakrishnan:
Learning Machines Implemented on Non-Deterministic Hardware. CoRR abs/1409.2620 (2014)
Coauthor Index
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