Random Hierarchies Professors in Global

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Panagiotis Charalampopoulos
King's College London United Kingdom
algorithms
regularity detection
sequence similarity
approximate pattern matching
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Aaron Gulliver
University of Victoria Canada
algorithms
iterative decoding
stochastic processes
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Souvik Dhara
Georgia Institute of Technology United States of America
random graphs
inference algorithms
stochastic processes
large-scale networks
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Khader Khadraoui
Laval University Canada
statistical inference
stochastic processes
high-dimensional probabilistic models
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Kavita Ramanan
Brown University United States of America
stochastic networks
stochastic analysis
stochastic processes
high-dimensional probability
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Ayman Gh.
Australian National University Australia
computational distributions
machine learning algorithms
ranking preference learning
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Nisheeth Vishnoi
Yale University United States of America
stochastic processes
algorithmic theory
approximation algorithms
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Nicholas Cook
Duke University Singapore
random hypergraphs
exponential random graph models
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Muller
Western University Canada
random graph theory
algorithms
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Matthew Jenssen
King's College London United Kingdom
random matrix theory
probabilistic
algorithms
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Jon Keating
University of Oxford United Kingdom
random matrix theory
stochastic analysis
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Joel Tropp
California Institute of Technology United States of America
random matrix theory
machine learning
numerical algorithms
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Alexander Strang
University of California, Berkeley United States of America
random graph theory
hierarchical bayesian inference
stochastic processes
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R. Kooij
Delft University of Technology Netherlands
randomness in computing
approximation algorithms
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Johannes Alt
University of Bonn Germany
random matrix theory
non-hermitian random matrices
eigenvalues of random graphs
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Nestor Parolya
Delft University of Technology Netherlands
random matrix theory
statistical machine learning
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Galyna Livshyts
Georgia Institute of Technology United States of America
random matrix theory
high-dimensional probability
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Mohammad Salavatipour
University of Alberta Canada
probabilistic randomized algorithms
approximation algorithms
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Eduard Belitser
Vrije Universiteit Amsterdam Netherlands
sequential algorithms
high-dimensional inference
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Wenpin Tang
Columbia University United States of America
probabilistic ranking models
machine learning
stochastic analysis
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Aditya Potukuchi
York University Canada
algorithmic sampling
algorithms
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