Multi View Learning Professors in Global

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Yuhong Guo
Carleton University Canada
self-supervised learning
computer vision
representation learning
semi-supervised learning
few-shot learning
reinforcement learning
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Yuhong Guo
Carleton University Canada
self-supervised learning
computer vision
representation learning
semi-supervised learning
few-shot learning
reinforcement learning
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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
cognitive learning
perceptual learning
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Yinbei Li
Singapore Institute of Technology Singapore
multimodal perception
imitation learning
robot learning
reinforcement learning
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Yichen Zhang
Purdue University United States of America
multi-task learning
distributed learning
reinforcement learning
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Giorgia Ramponi
University of Zurich Switzerland
multi-agent learning
imitation learning
reinforcement learning
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Jennifer Howell
University of Western Australia Australia
virtual learning
augmented learning
online learning
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Nicholas Rhinehart
University of Toronto Canada
imitation learning
robot learning
reinforcement learning
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Yuri Boykov
University of Waterloo Canada
self-supervised learning
computer vision
semi-supervised learning
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Christian Stöhr
Chalmers University of Technology Sweden
hybrid learning
digital learning
online learning
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Ying Wu
Northwestern University United States of America
multi-modal perception
computer vision
statistical learning
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Rudolf Lioutikov
University of Texas at Austin United States of America
imitation learning
structure learning
reinforcement learning
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Arthur Galamba
King's College London United Kingdom
hybrid learning
collaborative learning
online learning
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Pascal Poupart
University of Waterloo Canada
self-supervised learning
shot learning
reinforcement learning
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Iro Laina
University of Oxford United Kingdom
self-supervised learning
computer vision
language-supervised learning
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Yaoliang Yu
University of Waterloo Canada
computer vision
representation learning
distributed learning
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Mengye Ren
New York University United States of America
computer vision
representation learning
few-shot learning
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Minjie Xing
University of Manchester United Kingdom
multimodal language teaching
interactive learning
cooperative learning
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Alexander Rakhlin
Massachusetts Institute of Technology United States of America
reinforcement learning
online learning
statistical learning
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Pratheepa Jeganathan
McMaster University Canada
multi-view learning
statistical learning
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Mårten Björkman
KTH Royal Institute of Technology Sweden
multi-view computer vision
perception learning
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