Efficient Algorithmic Techniques For Processing High Dimensional Data Sets Professors in Global

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Debdeep Pati
University of Wisconsin–Madison United States of America
high dimensional network analysis
high-dimensional applications
efficient bayesian computation
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Dimosthenis Pasadakis
Università della Svizzera italiana Switzerland
high-dimensional data analysis
extreme-scale computing
numerical algorithms
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Suchuan Dong
Purdue University United States of America
high-order numerical methods
high performance computing
algorithms for dynamic simulations
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Uwe Naumann
RWTH Aachen University Germany
high-performance computing
optimization techniques
numerical algorithms
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Moses Charikar
Stanford University United States of America
efficient algorithmic techniques for processing high-dimensional data sets
efficient algorithms for computational problems in high-dimensional statistics
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Aravindan Vijayaraghavan
Northwestern University United States of America
high-dimensional data analysis
efficient algorithms
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Lars Karlsson
Umeå University Sweden
efficient algorithms
high-performance computing
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Dennis Fok
Erasmus University Rotterdam Netherlands
high-dimensional data
efficient estimation techniques
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Lingzhou Xue
Pennsylvania State University United States of America
high-dimensional data
large-scale optimization
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Sujay Sanghavi
University of Texas at Austin United States of America
high-dimensional data analysis
optimization algorithms
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Professorship Biometry Molecular Medicine
Ludwig Maximilian University of Munich Germany
high-dimensional data
high-throughput molecular data
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Nick Yakovets
Eindhoven University of Technology Belgium
high-performance data processing
data-intensive systems
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Xuewen Lu
University of Calgary Canada
high-dimensional data analysis
big data analysis
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Chad Schafer
Carnegie Mellon University United States of America
high-dimensional data
complex data structures
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Vladimir Okhmatovski
University of Manitoba Canada
high-performance computing
fast algorithms
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Bernd Dammann
Technical University of Denmark Denmark
high-performance computing
large scale computations
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Eleni Drinea
Columbia University United States of America
algorithms for big data
dimensionality reduction techniques
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Iadh Ounis
University of Glasgow United Kingdom
efficient architectures for large-scale information retrieval systems
big data information retrieval
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James Nichols
Australian National University Australia
high dimensional statistics
high dimensional approximation theory
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Laura Grigori
École Polytechnique Fédérale de Lausanne Switzerland
high dimensional problems
high performance computing
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Mehrdad Mahdavi
Pennsylvania State University United States of America
high-dimensional learning
large-scale optimization
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