Large Random Matrices Professors in Global

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Gunnar Martinsson
University of Texas at Austin United States of America
efficient algorithms for large data sets
randomized methods
structured matrix computations
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Roger Ghanem
University of Southern California United States of America
probabilistic multi-scale modeling
probabilistic modeling
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Roger Ghanem
University of Southern California United States of America
probabilistic multi-scale modeling
probabilistic modeling
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Dmitry Belyaev
University of Oxford United Kingdom
random growth models
random functions
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Nicholas Cook
Duke University Singapore
large deviations theory
random hypergraphs
exponential random graph models
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Eleni Drinea
Columbia University United States of America
randomized graph algorithms
algorithms for big data
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Eleni Drinea
Columbia University United States of America
randomized graph algorithms
algorithms for big data
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Max Welling
University of Amsterdam Netherlands
probabilistic models
big data
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Bryon Aragam
University of Chicago Booth School of Business United States of America
probabilistic modeling
deep generative models
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Elizaveta Rebrova
Princeton University United States of America
randomized algorithms
high-dimensional probability
non-asymptotic random matrix theory
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Elizaveta Rebrova
Princeton University United States of America
randomized algorithms
high-dimensional probability
non-asymptotic random matrix theory
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Jan Ambjørn
University of Copenhagen Denmark
matrix models
random surfaces
random paths
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Lei Ying
University of Michigan United States of America
large-scale graph mining
large-scale computing systems
large-scale communication systems
big data
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Xiucai Ding
University of California, Davis United States of America
applied random matrix theory
large foundation models
randomized numerical linear algebra
high-dimensional statistics
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Shaun Fallat
University of Regina Canada
matrix theory
combinatorial matrix analysis
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Yuqi Gu
Columbia University United States of America
deep generative models
probabilistic graphical models
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Guang Cheng
Purdue University United States of America
high dimensional statistical inferences
big data
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Jianliang Qian
Michigan State University United States of America
big data analysis
fast algorithms
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Jianliang Qian
Michigan State University United States of America
big data analysis
fast algorithms
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Takashi Owada
Purdue University United States of America
random topology
random graph theory
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Mingyuan Zhou
University of Texas at Austin United States of America
probabilistic machine learning
deep neural networks
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