Online Optimization Learning Professors in Global

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Kalyanmoy Deb
Michigan State University United States of America
computational optimization
process optimization
multi-objective optimization
hybrid optimization algorithms
meta-modeling optimization
evolutionary multi-objective optimization
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Albert Berahas
University of Michigan United States of America
machine learning optimization
stochastic optimization
distributed optimization
nonlinear optimization
constrained optimization
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
optimization algorithms
stochastic optimization
distributed optimization
nonlinear optimization
constrained optimization
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Alexander Rakhlin
Massachusetts Institute of Technology United States of America
online learning
optimization
reinforcement learning
statistical learning
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Siva Maguluri
Georgia Institute of Technology United States of America
optimization
stochastic optimization
distributed optimization
reinforcement learning
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Eric Kerrigan
Imperial College London United Kingdom
multi-objective optimization
dynamic optimization
numerical optimization methods
control optimization
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Adam Wierman
California Institute of Technology United States of America
online optimization
online learning
online algorithms
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Adam Wierman
California Institute of Technology United States of America
online optimization
online learning
online algorithms
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Adam Wierman
California Institute of Technology United States of America
online optimization
online learning
online algorithms
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Rad Niazadeh
University of Chicago Booth School of Business United States of America
online learning theory
online algorithms
optimization
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Sahil Singla
Georgia Institute of Technology United States of America
online learning
online algorithms
stochastic optimization
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Ruth Misener
Imperial College London United Kingdom
optimization models
computational optimization
data-driven optimization
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Dick Den Hertog
University of Amsterdam Netherlands
optimization in machine learning
linear optimization
nonlinear optimization
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Mehrdad Mahdavi
Pennsylvania State University United States of America
online learning
distributed optimization
large-scale optimization
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Bissan Ghaddar
Western University Canada
optimization models
transportation network optimization
energy optimization
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Nathaniel Bastian
Pennsylvania State University United States of America
optimization
multiple objective optimization
computational stochastic optimization
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John Jørgensen
Technical University of Denmark Denmark
numerical optimization
process optimization
dynamic optimization
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Yashar Pourrahimian
University of Alberta Canada
optimization
mining optimization
data-driven optimization
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Cynthia Vinzant
University of Washington United States of America
mathematical optimization
linear optimization
combinatorial optimization
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Jeremy Chen
National University of Singapore Singapore
mathematical optimization
design optimization
statistical learning
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Siva Maguluri
Georgia Institute of Technology United States of America
optimization
reinforcement learning
revenue optimization
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