Randomized Computation Professors in Global

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Xiucai Ding
University of California, Davis United States of America
randomized numerical linear algebra
stochastic optimization
scalable computation
applied random matrix theory
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Scott Schmidler
Duke University Singapore
probabilistic machine learning
computational biology
bayesian computation
computational immunology
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Michael Mitzenmacher
Harvard John Paulson School of Engineering and Applied Sciences United States of America
random processes
computer algorithms
machine learning
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Brokoslaw Laschowski
University of Toronto Canada
neural computation
machine learning
neural networks
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Michał Dereziński
University of Michigan United States of America
randomized numerical linear algebra
machine learning
random matrix theory
stochastic optimization
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Marylyn Ritchie
University of Pennsylvania United States of America
evolutionary computation
computational genomics
machine learning
computational biology
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Kay Wiese
Simon Fraser University Canada
evolutionary computation
machine learning
computational intelligence
computational biology
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Antti Knowles
University of Geneva Switzerland
random matrices
random graphs
stochastic processes
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Satish Thittamaranahalli
University of Southern California United States of America
machine learning
approximation and randomization
probabilistic reasoning
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Christoffer Back
University of Copenhagen Denmark
machine learning
probabilistic inference
stochastic processes
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Mohamed Abdelfattah
Cornell University Netherlands
machine learning
automated machine learning
neural networks
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Alexander Hartemink
Duke University Singapore
machine learning
computational biology
computational neurobiology
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Risto Miikkulainen
University of Texas at Austin United States of America
machine learning
computational biology
neural networks
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Stuart Russell
University of California, Berkeley United States of America
machine learning
probabilistic reasoning
real-time decision making
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Yee Teh
University of Oxford United Kingdom
computational statistics
machine learning
large scale machine learning
probabilistic learning
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Shawn Graham
Carleton University Canada
machine learning
computational creativity
neural networks
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A.c.c. Coolen
Radboud University Netherlands
random networks
machine learning
stochastic processes
neural networks
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Eliezer Upfal
Brown University United States of America
randomized algorithms
computational statistics
stochastic optimization
computational biology
probabilistic analysis
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James Spall
Johns Hopkins University United States of America
stochastic optimization
neural networks
stochastic systems
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James Spall
Johns Hopkins University United States of America
stochastic optimization
neural networks
stochastic systems
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Ingemar Kaj
Uppsala University Sweden
random fields
stochastic models
stochastic processes
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