Efficient Algorithms For Computational Problems In High Dimensional Statistics Professors in Global

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Suchuan Dong
Purdue University United States of America
algorithms for dynamic simulations
high-order numerical methods
high performance computing
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Debdeep Pati
University of Wisconsin–Madison United States of America
efficient bayesian computation
high dimensional network analysis
high-dimensional applications
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Ilias Diakonikolas
University of Wisconsin–Madison United States of America
high-dimensional robust statistics
data-driven algorithm design
algorithms
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Nicole Wein
University of Michigan United States of America
dynamic algorithms
distributed algorithms
distance-estimation algorithms
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Piotr Indyk
Massachusetts Institute of Technology United States of America
high-dimensional computational geometry
data stream algorithms
machine learning algorithms
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
optimization algorithms
distributed optimization
stochastic optimization
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Mehrdad Mahdavi
Pennsylvania State University United States of America
large-scale optimization
high-dimensional learning
distributed optimization
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Gara Pruesse
Vancouver Island University Canada
optimization algorithms
discrete algorithms
approximation algorithms
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Anirudh Subramanyam
Pennsylvania State University United States of America
high-performance computing
stochastic optimization
robust optimization
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Danupon Na Nongkai
KTH Royal Institute of Technology Sweden
quantum algorithms
data stream algorithms
approximation algorithms
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Panos Parpas
Imperial College London United Kingdom
computational optimization
mathematical optimization
algorithms
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Hossein Hashemi Doulabi
Concordia University Canada
large-scale optimization
stochastic optimization
robust optimization
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Kai James
Georgia Institute of Technology United States of America
high-fidelity computational models
numerical optimization
algorithms
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Alexandre Jacquillat
Massachusetts Institute of Technology United States of America
large-scale optimization
stochastic optimization
integer optimization
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Fernando Ordonez
University of Southern California United States of America
high performance computing
robust optimization
algorithms
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David Shmoys
Cornell University Netherlands
discrete optimization problems
approximation algorithms
stochastic optimization
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Yan Li
Texas A&M University United States of America
dynamic optimization
stochastic optimization
robust optimization
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Phebe Vayanos
University of Southern California United States of America
stochastic optimization
robust optimization
integer optimization
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Shixuan Zhang
Texas A&M University United States of America
stochastic optimization
robust optimization
integer optimization
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Chaoyue Zhao
University of Washington United States of America
stochastic optimization
robust optimization
data-driven optimization
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Xu Zhou
Imperial College London United Kingdom
distributed optimization
stochastic optimization
robust optimization
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