Semi Supervised Learning Professors in Global

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Yuhong Guo
Carleton University Canada
semi-supervised learning
self-supervised learning
weakly supervised learning
unsupervised learning
federated learning
representation learning
few-shot learning
continual learning
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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
cognitive learning
perceptual learning
transfer learning
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Pieter Abbeel
University of California, Berkeley United States of America
unsupervised learning
imitation learning
meta-learning
transfer learning
deep learning
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Yuri Boykov
University of Waterloo Canada
semi-supervised learning
self-supervised learning
weakly supervised learning
unsupervised learning
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Tamara Van Gog
Utrecht University Netherlands
self-regulated learning
multimedia learning
example-based learning
learning
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Fei Wang
Cornell University Netherlands
multi-modal learning
meta-learning
federated learning
transfer learning
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Arthur Galamba
King's College London United Kingdom
hybrid learning
collaborative learning
stem learning
online learning
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Christian Stöhr
Chalmers University of Technology Sweden
digital learning
hybrid learning
technology-enhanced learning
online learning
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Il-min Kim
Queen's University Canada
distributed learning
federated learning
few-shot learning
continual learning
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Ferenc Huszár
University of Cambridge United Kingdom
meta-learning
transfer learning
representation learning
deep learning
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Mengye Ren
New York University United States of America
meta-learning
representation learning
few-shot learning
continual learning
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Arash Amini
University of California Los Angeles United States of America
semi-supervised learning
unsupervised learning
representation learning
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Iro Laina
University of Oxford United Kingdom
self-supervised learning
language-supervised learning
unsupervised learning
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Siamak Mehrkanoon
Utrecht University Netherlands
semi-supervised learning
unsupervised learning
deep learning
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Randall Balestriero
Brown University United States of America
self-supervised learning
representation learning
deep learning
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Sarthak Yadav
Aalborg University Denmark
self-supervised learning
representation learning
deep learning
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Xiaochen Yang
University of Glasgow United Kingdom
self-supervised learning
statistical machine learning
few-shot learning
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Vinay Gogineni
University of Southern Denmark Denmark
self-supervised learning
continual learning
meta learning
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Carlo Ciliberto
University College London United Kingdom
multi-task learning
meta-learning
statistical learning theory
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Marie-soleil Beaudoin
Dalhousie University Canada
self-regulated learning
blended learning
online learning
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Nikki Lobczowski
McGill University Canada
self-regulated learning
social regulation learning
collaborative learning
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