Sparse Machine Learning Professors in Global

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Irina Rish
University of Montreal Canada
sparse modeling
machine learning
deep learning
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Line Clemmensen
Technical University of Denmark Denmark
sparse methods
machine learning
deep learning
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Danica Sutherland
University of British Columbia Canada
statistical machine learning
machine learning
theoretical machine learning
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Samy Bengio
École Polytechnique Fédérale de Lausanne Switzerland
statistical machine learning
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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Yoshua Bengio
University of Montreal Canada
machine learning
statistical learning algorithms
deep learning
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Ramandeep Randhawa
University of Southern California United States of America
machine learning
deep learning
stochastic modeling
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Samir Maity
Aalborg University Denmark
machine learning
deep learning
predictive modeling
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John Doe
University of Wisconsin–Madison United States of America
machine learning
deep learning
predictive modeling
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Mogana Ganggayah
Monash University Australia
machine learning
deep learning
predictive modeling
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Titouan Muzellec
University of Vienna Austria
machine learning
statistical learning
predictive modeling
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Guang Lin
Purdue University United States of America
machine learning
statistical learning
predictive modeling
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Laurence Frank
Utrecht University Netherlands
machine learning
statistical learning
predictive modelling
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Aboelmagd Noureldin
Queen's University Canada
machine intelligence
machine vision
deep learning
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Guillaume Obozinski
École Polytechnique Fédérale de Lausanne Switzerland
sparse modeling
machine learning
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Tatjana Pavlenko
Uppsala University Sweden
sparse signal detection
statistical machine learning
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Juan Vera Lizcano
Tilburg University Netherlands
sparse methods
machine learning
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Xiaofei Shi
University of Toronto Canada
sparse recovery
machine learning
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Zoltán Szabó
London School of Economics and Political Science United Kingdom
structured sparsity
statistical machine learning
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Piotr Indyk
Massachusetts Institute of Technology United States of America
sparse recovery
machine learning algorithms
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Mahdi Cheraghchi
Imperial College London United Kingdom
sparse recovery
randomized computation
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