Hardware Acceleration For Machine Learning Professors in Global

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Jiaqi Gu
Arizona State University China
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gpu acceleration
emerging hardware design for efficient computing
efficient ai hardware design
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Anatole Von Lilienfeld
University of Toronto Canada
high-performance computing
machine learning
quantum machine learning
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Eric Darve
Stanford University United States of America
high-performance computing
machine learning
gpu computing
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Tze Low
Carnegie Mellon University United States of America
hardware
machine learning
parallel high-performance computing
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George Amvrosiadis
Carnegie Mellon University United States of America
high performance computing
machine learning
scalable machine learning
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Ian Jeffrey
University of Manitoba Canada
high-performance computing
gpu computing
applied machine learning
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Bernd Dammann
Technical University of Denmark Denmark
high-performance computing
gpu computing
large scale computations
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Simon Mcintosh-smith
University of Bristol United Kingdom
high performance computing
gpu computing
multi-core processors
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Richard D'arcy
University of Oxford United Kingdom
novel accelerators
plasma accelerators
conventional accelerators
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Danica Sutherland
University of British Columbia Canada
machine learning
statistical machine learning
theoretical machine learning
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David Pan
University of Texas at Austin United States of America
hardware acceleration
efficient machine learning
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Lei Zhang
University of Regina Canada
hardware acceleration
machine learning
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David Pan
University of Texas at Austin United States of America
hardware acceleration
machine learning
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Aditya Akella
University of Texas at Austin United States of America
hardware acceleration
machine learning
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Young Cho
University of Southern California United States of America
hardware acceleration
machine learning
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David Pan
University of Texas at Austin United States of America
hardware acceleration
machine learning
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Brandon Reagen
New York University Tandon School of Engineering United States of America
hardware acceleration
machine learning
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Gary Grewal
University of Guelph Canada
hardware acceleration
machine learning
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Timothy Rogers
Purdue University United States of America
hardware accelerators
hardware
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Yuan Li
Singapore Institute of Technology Singapore
hardware accelerator
machine learning
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Benjamin Owen
University of Edinburgh United Kingdom
gpu acceleration
machine learning
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