Federated Learning Professors in Global

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Pieter Abbeel
University of California, Berkeley United States of America
reinforcement learning
transfer learning
imitation learning
meta-learning
deep learning
unsupervised learning
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Antoine Van Den Beemt
Eindhoven University of Technology Belgium
networked learning
transdisciplinary learning
technology enhanced learning
challenge-based learning
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Siamak Mehrkanoon
Utrecht University Netherlands
semi-supervised learning
deep learning
unsupervised learning
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Lone Hersted
Aalborg University Denmark
organizational learning
learning processes
action learning
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Morten Sørensen
Aarhus University Denmark
adult learning
learning design
game-based learning
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William Cope
University of Illinois United States of America
technology-mediated learning
machine learning in education
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Vincent Hoogerheide
Utrecht University Netherlands
self-regulated learning
learning-by-teaching
video-based learning
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Olof Bälter
Royal Institute of Technology Sweden
learning engineering
technology enhanced learning
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Richard Noss
University College London United Kingdom
computational environments for learning
technology enhanced learning
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Richard Ivry
University of California, Berkeley United States of America
motor learning
implicit learning
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John Schulz
University of Southampton United Kingdom
online learning
e-learning
video-based learning
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Nicholas Rhinehart
University of Toronto Canada
reinforcement learning
robot learning
imitation learning
deep learning
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Louisa Penfold
Harvard Graduate School of Education United States of America
child-centered learning
informal learning
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Marije Michel
University of Groningen Netherlands
language learning
digitally mediated language learning
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Yuhong Guo
Carleton University Canada
federated learning
reinforcement learning
continual learning
representation learning
self-supervised learning
active learning
semi-supervised learning
unsupervised learning
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Yuri Boykov
University of Waterloo Canada
self-supervised learning
semi-supervised learning
unsupervised learning
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Arash Amini
University of California Los Angeles United States of America
representation learning
semi-supervised learning
unsupervised learning
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Yuhong Guo
Carleton University Canada
federated learning
reinforcement learning
continual learning
representation learning
self-supervised learning
active learning
semi-supervised learning
unsupervised learning
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Denise Chalmers
University of Western Australia Australia
e-learning
teaching and learning
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Dingxuan Zhou
University of Sydney Australia
learning theory
deep learning
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Linus Ericsson
University of Glasgow United Kingdom
representation learning
automated machine learning
multi-modal learning
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