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2020 – today
- 2024
[i10]Suharsh Sivakumar, Jonathan Shen, Rajat Monga:
TRACE: A Time-Relational Approximate Cubing Engine for Fast Data Insights. CoRR abs/2401.06336 (2024)
2010 – 2019
- 2019
- [c10]Akshay Agrawal, Akshay Naresh Modi, Alexandre Passos, Allen Lavoie, Ashish Agarwal, Asim Shankar, Igor Ganichev, Josh Levenberg, Mingsheng Hong, Rajat Monga, Shanqing Cai:
TensorFlow Eager: A multi-stage, Python-embedded DSL for machine learning. SysML 2019 - [c9]Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viégas, Martin Wattenberg:
TensorFlow.js: Machine Learning For The Web and Beyond. SysML 2019 - [i9]Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viégas, Martin Wattenberg:
TensorFlow.js: Machine Learning for the Web and Beyond. CoRR abs/1901.05350 (2019) - [i8]Akshay Agrawal, Akshay Naresh Modi, Alexandre Passos, Allen Lavoie, Ashish Agarwal, Asim Shankar, Igor Ganichev, Josh Levenberg, Mingsheng Hong, Rajat Monga, Shanqing Cai:
TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning. CoRR abs/1903.01855 (2019) - [i7]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li
, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - 2018
- [c8]Yuan Yu, Martín Abadi, Paul Barham, Eugene Brevdo, Mike Burrows, Andy Davis, Jeff Dean, Sanjay Ghemawat, Tim Harley, Peter Hawkins, Michael Isard, Manjunath Kudlur, Rajat Monga, Derek Gordon Murray, Xiaoqiang Zheng:
Dynamic control flow in large-scale machine learning. EuroSys 2018: 18:1-18:15 - [i6]Yuan Yu, Martín Abadi, Paul Barham, Eugene Brevdo, Mike Burrows, Andy Davis, Jeff Dean, Sanjay Ghemawat, Tim Harley, Peter Hawkins, Michael Isard, Manjunath Kudlur, Rajat Monga, Derek Gordon Murray, Xiaoqiang Zheng:
Dynamic Control Flow in Large-Scale Machine Learning. CoRR abs/1805.01772 (2018) - 2016
- [c7]Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zheng:
TensorFlow: A System for Large-Scale Machine Learning. OSDI 2016: 265-283 - [i5]Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng:
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. CoRR abs/1603.04467 (2016) - [i4]Jianmin Chen, Rajat Monga, Samy Bengio, Rafal Józefowicz:
Revisiting Distributed Synchronous SGD. CoRR abs/1604.00981 (2016) - [i3]Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zhang:
TensorFlow: A system for large-scale machine learning. CoRR abs/1605.08695 (2016) - 2015
- [c6]Joe Yue-Hei Ng, Matthew J. Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici:
Beyond short snippets: Deep networks for video classification. CVPR 2015: 4694-4702 - [c5]Sudheendra Vijayanarasimhan, Jonathon Shlens, Rajat Monga, Jay Yagnik:
Deep Networks With Large Output Spaces. ICLR (Workshop) 2015 - [i2]Joe Yue-Hei Ng, Matthew J. Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici:
Beyond Short Snippets: Deep Networks for Video Classification. CoRR abs/1503.08909 (2015) - 2014
- [c4]Hasim Sak, Oriol Vinyals, Georg Heigold, Andrew W. Senior, Erik McDermott, Rajat Monga, Mark Z. Mao:
Sequence discriminative distributed training of long short-term memory recurrent neural networks. INTERSPEECH 2014: 1209-1213 - 2013
- [c3]Matthew D. Zeiler, Marc'Aurelio Ranzato, Rajat Monga, Mark Z. Mao, K. Yang, Quoc Viet Le, Patrick Nguyen, Andrew W. Senior, Vincent Vanhoucke, Jeffrey Dean, Geoffrey E. Hinton:
On rectified linear units for speech processing. ICASSP 2013: 3517-3521 - 2012
- [c2]Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng:
Building high-level features using large scale unsupervised learning. ICML 2012 - [c1]Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc'Aurelio Ranzato, Andrew W. Senior, Paul A. Tucker, Ke Yang, Andrew Y. Ng:
Large Scale Distributed Deep Networks. NIPS 2012: 1232-1240 - 2011
- [i1]Quoc V. Le, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Marc'Aurelio Ranzato, Jeffrey Dean, Andrew Y. Ng:
Building high-level features using large scale unsupervised learning. CoRR abs/1112.6209 (2011)
Coauthor Index
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last updated on 2024-10-07 22:09 CEST by the dblp team
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