Bayesian Optimisation Professors in Global

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Albert Berahas
University of Michigan United States of America
stochastic optimization
machine learning optimization
constrained optimization
nonlinear optimization
distributed optimization
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
stochastic optimization
optimization algorithms
machine learning
constrained optimization
nonlinear optimization
distributed optimization
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Jeya Jeyakumar
University of New South Wales Australia
mathematical optimization
machine learning
nonlinear optimization
robust optimization
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Bartolomeo Stellato
Princeton University United States of America
mathematical optimization
machine learning
large scale optimization
differentiable optimization
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Phebe Vayanos
University of Southern California United States of America
stochastic optimization
machine learning
robust optimization
integer optimization
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Phebe Vayanos
University of Southern California United States of America
stochastic optimization
machine learning
robust optimization
integer optimization
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Phebe Vayanos
University of Southern California United States of America
stochastic optimization
machine learning
robust optimization
integer optimization
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Jelena Diakonikolas
University of Wisconsin–Madison United States of America
large-scale optimization
machine learning
first-order optimization algorithms
non-convex optimization
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Geoff Pleiss
University of British Columbia Canada
bayesian optimization
machine learning
probabilistic machine learning
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Charbel Farhat
Stanford University United States of America
bayesian optimization
probabilistic machine learning
computational algorithms
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Aban Ansari-önnestam
Linköping University Sweden
mathematical optimization
machine learning
continuous optimization
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Michael Morin
Laval University Canada
mathematical optimization
machine learning
combinatorial network optimization
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David Scheinker
Stanford University United States of America
mathematical optimization
machine learning
probabilistic modeling
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Miaolan Xie
Purdue University United States of America
stochastic optimization
machine learning
nonlinear optimization
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Brenda Dietrich
Cornell University Netherlands
mathematical optimization
machine learning
applied optimization
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Hossein Hashemi Doulabi
Concordia University Canada
stochastic optimization
large-scale optimization
robust optimization
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Alexandre Jacquillat
Massachusetts Institute of Technology United States of America
stochastic optimization
large-scale optimization
integer optimization
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Nathan Kallus
Cornell University Netherlands
stochastic optimization
machine learning
optimization
robust optimization
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Zhe Zhang
Purdue University United States of America
stochastic optimization
machine learning
distributed optimization
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Arkadi Nemirovski
Georgia Institute of Technology United States of America
stochastic optimization
continuous optimization
optimization theory
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Chuan He
Linköping University Sweden
large-scale optimization
machine learning
continuous optimization
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