J
Jeffrey Dean
Researcher at Google
Publications - 255
Citations - 207859
Jeffrey Dean is an academic researcher from Google. The author has contributed to research in topics: Deep learning & Web search query. The author has an hindex of 83, co-authored 242 publications receiving 179031 citations. Previous affiliations of Jeffrey Dean include University of Washington & World Health Organization.
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Patent
Method for scheduling threads in a multithreaded processor
TL;DR: In this article, a method for scheduling execution of a plurality of threads executed in a multithreaded processor is presented. But the method is limited to a single thread and it is not suitable for multi-threaded systems.
Proceedings ArticleDOI
Vortex: an optimizing compiler for object-oriented languages
TL;DR: The Vortex compiler infrastructure is developed, a language-independent optimizing compiler for object-oriented languages, with front-ends for Cecil, C++, Java, and Modula-3, and the results of experiments assessing the effectiveness of different combinations of optimizations on sizable applications across these four languages are reported.
Proceedings Article
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Noam Shazeer,Azalia Mirhoseini,Krzysztof Maziarz,Andy Davis,Quoc V. Le,Geoffrey E. Hinton,Jeffrey Dean +6 more
TL;DR: In this paper, a sparsely-gated mixture-of-experts (MoE) layer is proposed to increase the capacity of a neural network to absorb information without a proportional increase in computation.
Journal ArticleDOI
Epi Info: a general-purpose microcomputer program for public health information systems.
TL;DR: Epi Info is a general-purpose set of computer programs for word processing, database management, statistics, and graphics developed over the past five years at the Centers for Disease Control and the World Health Organization that allow rapid questionnaire construction, data entry, and analysis during epidemic investigation.
Patent
Encoding and adaptive, scalable accessing of distributed models
Franz Josef Och,Jeffrey Dean,Thorsten Brants,Alexander Franz,Jay Ponte,Peng Xu,Sha-Mayn Teh,Jeffrey Chin,Ignacio Thayer,Anton Carver,Daniel Rosart,John S. Hawkins,Karel Driesen +12 more
TL;DR: In this article, the authors present systems, methods, and apparatus for accessing distributed models in automated machine processing, including using large language models in machine translation, speech recognition and other applications.