Investor Learning Professors in Global

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Yuhong Guo
Carleton University Canada
reinforcement learning
continual learning
representation learning
machine learning
self-supervised learning
federated learning
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Yuhong Guo
Carleton University Canada
reinforcement learning
continual learning
representation learning
machine learning
self-supervised learning
federated learning
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Pascal Poupart
University of Waterloo Canada
reinforcement learning
continual learning
shot learning
machine learning
self-supervised learning
causal learning
federated learning
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Il-min Kim
Queen's University Canada
continual learning
distributed learning
federated learning
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Yaoliang Yu
University of Waterloo Canada
representation learning
distributed learning
machine learning
federated learning
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Sascha Schneider
University of Zurich Switzerland
social learning
cognitive learning
emotional learning
motivational learning
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Fernando Olivera
Western University Canada
individual learning
group learning
learning processes
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Elizabeth Brannon
University of Pennsylvania United States of America
memory learning
animal learning behavior
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Mengye Ren
New York University United States of America
continual learning
representation learning
machine learning
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Becket Ebitz
University of Montreal Canada
learning processes
learning memory
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Jörgen From
Umeå University Sweden
field learning
hybrid learning
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Vinay Gogineni
University of Southern Denmark Denmark
continual learning
machine learning
self-supervised learning
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Ulrik Brandi
Aarhus University Denmark
learning
learning organisations
organisational learning
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C. Green
University of Wisconsin–Madison United States of America
human learning
motor learning
cognitive learning
transfer learning
depth learning
perceptual learning
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Sarthak Yadav
Aalborg University Denmark
representation learning
deep learning
self-supervised learning
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Randall Balestriero
Brown University United States of America
representation learning
deep learning
self-supervised learning
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Guillermo Sapiro
Duke University Singapore
dictionary learning
learning high dimensional data analysis
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Honglak Lee
University of Michigan United States of America
representation learning
deep learning
machine learning
large-scale learning
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Yue Tan
University of New South Wales Australia
representation learning
federated learning
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José Júnior
Uppsala University Sweden
distributed learning
machine learning
federated learning
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Adrian Edin
Linköping University Sweden
distributed learning
federated learning
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