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Xiaoqiang Zheng
Researcher at Google
Publications - 5
Citations - 27026
Xiaoqiang Zheng is an academic researcher from Google. The author has contributed to research in topics: Dataflow & Deep learning. The author has an hindex of 5, co-authored 5 publications receiving 22914 citations.
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Proceedings ArticleDOI
TensorFlow: a system for large-scale machine learning
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 G. Murray,Benoit Steiner,Paul A. Tucker,Vijay K. Vasudevan,Pete Warden,Martin Wicke,Yuan Yu,Xiaoqiang Zheng +21 more
TL;DR: TensorFlow as mentioned in this paper is a machine learning system that operates at large scale and in heterogeneous environments, using dataflow graphs to represent computation, shared state, and the operations that mutate that state.
Posted Content
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi,Ashish Agarwal,Paul Barham,Eugene Brevdo,Zhifeng Chen,Craig Citro,Greg S. Corrado,Andy Davis,Jeffrey Dean,Matthieu Devin,Sanjay Ghemawat,Ian Goodfellow,Andrew Harp,Geoffrey Irving,Michael Isard,Yangqing Jia,Rafal Jozefowicz,Lukasz Kaiser,Manjunath Kudlur,Josh Levenberg,Dan Mané,Rajat Monga,Sherry Moore,Derek G. Murray,Chris Olah,Mike Schuster,Jonathon Shlens,Benoit Steiner,Ilya Sutskever,Kunal Talwar,Paul A. Tucker,Vincent Vanhoucke,Vijay K. Vasudevan,Fernanda B. Viégas,Oriol Vinyals,Pete Warden,Martin Wattenberg,Martin Wicke,Yuan Yu,Xiaoqiang Zheng +39 more
TL;DR: The TensorFlow interface and an implementation of that interface that is built at Google are described, which has been used for conducting research and for deploying machine learning systems into production across more than a dozen areas of computer science and other fields.
Posted Content
TensorFlow: A system for large-scale machine learning
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 G. Murray,Benoit Steiner,Paul A. Tucker,Vijay K. Vasudevan,Pete Warden,Martin Wicke,Yuan Yu,Xiaoqiang Zheng +21 more
TL;DR: The TensorFlow dataflow model is described and the compelling performance that Tensor Flow achieves for several real-world applications is demonstrated.
Proceedings ArticleDOI
Dynamic control flow in large-scale machine learning
Yuan Yu,Martín Abadi,Paul Barham,Eugene Brevdo,Michael Burrows,Andy Davis,Jeffrey Dean,Sanjay Ghemawat,Tim Harley,Peter Hawkins,Michael Isard,Manjunath Kudlur,Rajat Monga,Derek G. Murray,Xiaoqiang Zheng +14 more
TL;DR: This paper describes the design of the programming model, and its implementation in TensorFlow, a distributed machine learning system, and describes the use of dataflow graphs to represent machine learning models, offering several distinctive features.
Proceedings ArticleDOI
Dynamic Control Flow in Large-Scale Machine Learning
Yuan Yu,Martín Abadi,Paul Barham,Eugene Brevdo,Michael Burrows,Andy Davis,Jeffrey Dean,Sanjay Ghemawat,Tim Harley,Peter Hawkins,Michael Isard,Manjunath Kudlur,Rajat Monga,Derek G. Murray,Xiaoqiang Zheng +14 more
TL;DR: The TensorFlow programming model as discussed by the authors extends the use of dataflow graphs to represent machine learning models, offering several distinctive features, such as the branches of conditionals and bodies of loops can be partitioned across many machines to run on a set of heterogeneous devices.