Randomized Linear Algebra Professors in Global

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Adji Dieng
Princeton University United States of America
probabilistic modeling
statistical machine learning
deep learning
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Guido Montufar
University of California Los Angeles United States of America
deep learning
artificial neural networks
algebraic statistics
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Alexandre Bouchard-côté
University of British Columbia Canada
probabilistic modelling
statistical machine learning
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Jonathan Weare
New York University United States of America
stochastic algorithms
statistical machine learning
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Bryon Aragam
University of Chicago Booth School of Business United States of America
probabilistic modeling
statistical machine learning
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Stephen Bach
Brown University United States of America
machine learning
statistical machine learning
statistical relational learning
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Frank Sottile
Texas A&M University United States of America
computational algebraic geometry
algebraic geometry
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Niclas Börlin
Umeå University Sweden
non-linear algorithms
non-linear estimation
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Christian Frier
Aalborg University Denmark
probabilistic modeling
stochastic modeling
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Christian Onof
Imperial College London United Kingdom
statistical machine learning
stochastic modeling
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Mert Sabuncu
Cornell University Netherlands
probabilistic modeling
applied machine learning
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Arno Onken
University of Edinburgh United Kingdom
machine learning
probabilistic modelling
deep learning
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Peng Liu
Linköping University Sweden
regression analysis
stochastic models
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Wenjuan Zhang
Warwick Business School United Kingdom
regression analysis
stochastic models
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Susan Cooper
University of Manitoba Canada
commutative algebra
combinatorial commutative algebra
algebraic geometry
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Ayman Gh.
Australian National University Australia
machine learning algorithms
deep learning
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David Poole
University of British Columbia Canada
relational learning
statistical relational ai
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Jianfeng Zhang
University of Southern California United States of America
stochastic analysis
stochastic numerics
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Hina Shaheen
University of Manitoba Canada
machine learning
statistical machine learning
computational modelling
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Chris De Sa
Cornell University Netherlands
stochastic algorithms
deep learning
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Chris De Sa
Cornell University Netherlands
stochastic algorithms
deep learning
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