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

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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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Gara Pruesse
Vancouver Island University Canada
optimization algorithms
discrete algorithms
approximation 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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Anirudh Subramanyam
Pennsylvania State University United States of America
high-performance computing
stochastic optimization
robust 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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Xu Zhou
Imperial College London United Kingdom
distributed optimization
stochastic optimization
robust 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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Chaoyue Zhao
University of Washington United States of America
stochastic optimization
robust optimization
data-driven 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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Phebe Vayanos
University of Southern California United States of America
stochastic optimization
robust optimization
integer 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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Phebe Vayanos
University of Southern California United States of America
stochastic optimization
robust optimization
integer optimization
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Moses Charikar
Stanford University United States of America
efficient algorithms for computational problems in high-dimensional statistics
efficient algorithmic techniques for processing high-dimensional data sets
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Chris De Sa
Cornell University Netherlands
high-performance machine learning
stochastic algorithms
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Chris De Sa
Cornell University Netherlands
high-performance machine learning
stochastic algorithms
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Bill Press
University of Texas at Austin United States of America
fast numerical statistical algorithms
computational statistical methods
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Ilias Diakonikolas
University of Wisconsin–Madison United States of America
high-dimensional robust statistics
data-driven algorithm design
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Andrew Holbrook
University of California Los Angeles United States of America
high-performance computing
computational statistics
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Yaoliang Yu
University of Waterloo Canada
optimization algorithms
robust stochastic optimization
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Michael Newton
University of Wisconsin–Madison United States of America
high-dimensional biostatistical inference
computational statistics
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Anindya Bhadra
Purdue University United States of America
high-dimensional complex data
computational statistics
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