Machine Learning Pipeline Optimization Professors in Global

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Kalyanmoy Deb
Michigan State University United States of America
computational optimization
process optimization
machine learning
hybrid optimization algorithms
meta-modeling optimization
multi-objective optimization
evolutionary multi-objective optimization
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
optimization algorithms
machine learning
nonlinear optimization
stochastic optimization
distributed optimization
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Bartolomeo Stellato
Princeton University United States of America
mathematical optimization
machine learning
large scale optimization
real-time embedded optimization
differentiable optimization
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Albert Berahas
University of Michigan United States of America
machine learning optimization
nonlinear optimization
stochastic optimization
distributed optimization
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Ruth Misener
Imperial College London United Kingdom
computational optimization
machine learning
optimization models
data-driven optimization
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Nathaniel Bastian
Pennsylvania State University United States of America
machine learning
multiple objective optimization
computational stochastic optimization
optimization
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John Chinneck
Carleton University Canada
nonlinear optimization
optimization
mixed integer optimization
feasibility optimization
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Eric Kerrigan
Imperial College London United Kingdom
multi-objective optimization
control optimization
dynamic optimization
numerical optimization methods
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Dick Den Hertog
University of Amsterdam Netherlands
optimization in machine learning
linear optimization
nonlinear optimization
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Dick Den Hertog
University of Amsterdam Netherlands
linear optimization
machine learning
nonlinear optimization
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Fengqi You
Cornell University Netherlands
supply chain optimization
optimization algorithms
machine learning
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Cynthia Vinzant
University of Washington United States of America
linear optimization
mathematical optimization
combinatorial optimization
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Jeya Jeyakumar
University of New South Wales Australia
mathematical optimization
machine learning
nonlinear optimization
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Yassine Yaakoubi
Concordia University Canada
machine learning-augmented optimization
supply value chain optimization
probabilistic machine learning
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Michael Morin
Laval University Canada
mathematical optimization
machine learning
combinatorial network optimization
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Michael Patriksson
University of Gothenburg Sweden
mathematical optimization
nonlinear optimization
combinatorial optimization
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Aban Ansari-önnestam
Linköping University Sweden
mathematical optimization
machine learning
continuous optimization
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Elad Hazan
Princeton University United States of America
machine learning
stochastic optimization
optimization
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Jessica Sorrell
Johns Hopkins University United States of America
machine learning algorithms
machine learning
machine learning theory
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Pascal Frossard
École Polytechnique Fédérale de Lausanne Switzerland
machine learning
network machine learning
optimization
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Molei Tao
Georgia Institute of Technology United States of America
machine learning
probabilistic machine learning
optimization
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