Hardware Aware Machine Learning Professors in Global

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Kristen Grauman
University of Texas at Austin United States of America
machine learning
interactive machine learning
machine perception
deep learning
visual recognition
computer vision
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Geoff Webb
Monash University Australia
machine learning
interactive machine learning
ensemble machine learning
bayesian machine learning
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Naveed Akhtar
University of Western Australia Australia
machine learning
adversarial machine learning
deep learning
computer vision
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Ke Chen
University of Manchester United Kingdom
machine learning
machine perception
pattern recognition
computer vision
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Benjamin Joffe
Georgia Institute of Technology United States of America
machine learning
robot learning
deep learning
computer vision
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Kin-choong Yow
University of Regina Canada
machine learning
deep learning
pattern recognition
computer vision
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Vishnu Boddeti
Michigan State University United States of America
machine learning
deep learning
pattern recognition
computer vision
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Joshua Peeples
Texas A&M University United States of America
machine learning
deep learning
pattern recognition
computer vision
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Divya Sharma
York University Canada
machine learning
deep learning
pattern recognition
computer vision
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Alexandra Branzan Albu
University of Victoria Canada
machine learning
deep learning
pattern recognition
computer vision
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Jessica Sorrell
Johns Hopkins University United States of America
machine learning
machine learning algorithms
machine learning theory
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Danica Sutherland
University of British Columbia Canada
machine learning
statistical machine learning
theoretical machine learning
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Yisong Yue
California Institute of Technology United States of America
machine learning
statistical machine learning
interactive machine learning
structured machine learning
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Pietro Perona
California Institute of Technology United States of America
machine learning
machine vision
visual recognition
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Gary Grewal
University of Guelph Canada
machine learning
hardware acceleration
deep learning
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Farhad Maleki
University of Calgary Canada
machine learning
applied machine learning
computer vision
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Sophia Wilson
University of Copenhagen Denmark
machine learning
resource efficient machine learning
data efficient machine learning
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Anatole Von Lilienfeld
University of Toronto Canada
machine learning
quantum machine learning
high-performance computing
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Samy Bengio
École Polytechnique Fédérale de Lausanne Switzerland
machine learning
statistical machine learning
deep learning
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Navid Azizan
Massachusetts Institute of Technology United States of America
machine learning
scientific machine learning
trustworthy machine learning
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Fons Van Der Sommen
Eindhoven University of Technology Belgium
machine learning
computer-aided detection
computer vision
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