Randomized Computation Professors in Global

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Ivan Kryven
Utrecht University Netherlands
randomized algorithms
random approximation algorithms
random graph representation
random matrices
stochastic analysis
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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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John Reif
Duke University Singapore
randomized algorithms
quantum computation
algebraic computation
optical computation
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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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Nazim Khan
University of Western Australia Australia
computational statistics
statistical computing
stochastic modelling
computational methods
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A.c.c. Coolen
Radboud University Netherlands
random networks
machine learning
stochastic processes
neural networks
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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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Yee Teh
University of Oxford United Kingdom
computational statistics
machine learning
large scale machine learning
probabilistic learning
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Kay Wiese
Simon Fraser University Canada
evolutionary computation
machine learning
computational intelligence
computational biology
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Scott Schmidler
Duke University Singapore
probabilistic machine learning
computational biology
bayesian computation
computational immunology
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Avi Wigderson
Institute for Advanced Study United States of America
randomness in computation
distributed computation
quantum computation
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Monika Eisenmann
Lund University Sweden
randomized algorithms
machine learning
stochastic numerical analysis
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Leo Benatar
Georgia Institute of Technology United States of America
randomized algorithms
random graphs
stochastic processes
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Krzysztof Latuszynski
University of Warwick United Kingdom
stochastic simulation
computational statistics
probabilistic algorithms
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Laurence Frank
Utrecht University Netherlands
randomized response
machine learning
predictive modelling
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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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Luke Miller
Radboud University Netherlands
neural computations
computational modeling
machine learning
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Qing Zhao
Cornell University Netherlands
computation
machine learning
stochastic optimization
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Ran Raz
Weizmann Institute of Science Israel
randomness
quantum computation
derandomization
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Satish Thittamaranahalli
University of Southern California United States of America
approximation randomization
machine learning
probabilistic reasoning
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Gareth Roberts
University of Warwick United Kingdom
stochastic simulation
computational statistics
stochastic processes
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