Optimizing Algorithms Professors in Global

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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
optimization algorithms
stochastic optimization
constrained optimization
distributed optimization
nonlinear optimization
machine learning
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Kalyanmoy Deb
Michigan State University United States of America
process optimization
hybrid optimization algorithms
computational optimization
multi-objective optimization
machine learning
meta-modeling optimization
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Albert Berahas
University of Michigan United States of America
machine learning optimization
stochastic optimization
constrained optimization
distributed optimization
nonlinear optimization
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Marc Renault
University of Wisconsin United States of America
analysis of algorithms
search algorithms
approximation algorithms
online algorithms
algorithm design
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Yinyu Ye
Stanford University United States of America
algorithm development
dynamic optimization
continuous optimization
machine learning
discrete optimization
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Elad Hazan
Princeton University United States of America
optimization
algorithms
stochastic optimization
machine learning
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Arkadi Nemirovski
Georgia Institute of Technology United States of America
algorithms
stochastic optimization
optimization theory
continuous optimization
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Nathan Kallus
Cornell University Netherlands
optimization
stochastic optimization
machine learning
robust optimization
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Eliezer Upfal
Brown University United States of America
analysis of algorithms
randomized algorithms
stochastic optimization
algorithm design
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Kent Quanrud
Purdue University United States of America
optimization
approximation algorithms
algorithm design
combinatorial optimization
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Manuel Lopez-ibanez
University of Manchester United Kingdom
optimisation
multi-objective optimisation
combinatorial optimisation
machine learning
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Dick Den Hertog
University of Amsterdam Netherlands
optimization in machine learning
linear optimization
nonlinear optimization
robust optimization
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Chaitanya Swamy
University of Waterloo Canada
stochastic optimization
approximation algorithms
online algorithms
combinatorial optimization
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Marina Epelman
University of Michigan United States of America
mathematical optimization
integer optimization
optimization under uncertainty
discrete optimization
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Cynthia Vinzant
University of Washington United States of America
mathematical optimization
linear optimization
combinatorial optimization
discrete optimization
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Mark Daskin
University of Michigan United States of America
mathematical optimization
integer optimization
discrete optimization
network flows optimization
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Viswanath Nagarajan
University of Michigan United States of America
algorithms
stochastic optimization
machine learning
discrete optimization
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Shixuan Zhang
Texas A&M University United States of America
integer optimization
stochastic optimization
polynomial optimization
robust optimization
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Chuan He
Linköping University Sweden
large-scale optimization
continuous optimization
decentralized optimization
machine learning
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Nima Anari
Stanford University United States of America
randomized algorithms
algorithm design
combinatorial optimization
machine learning
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Jeya Jeyakumar
University of New South Wales Australia
mathematical optimization
nonlinear optimization
machine learning
robust optimization
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