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Randomised Algorithms
Randomised Algorithms Professors in Global
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Professor
Nicole Wein
University of Michigan
United States of America
parameterized algorithms
distributed algorithms
online algorithms
dynamic algorithms
distance-estimation algorithms
graph algorithms
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Professor
Michael Mitzenmacher
Harvard John Paulson School of Engineering and Applied Sciences
United States of America
computer algorithms
random processes
machine learning
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Professor
Max Ward-graham
University of Western Australia
Australia
algorithms
rna algorithms
machine learning
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Professor
Graham Farr
Monash University
Australia
algorithms
enumeration algorithm
graph algorithms
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Professor
Tuğkan Batu
London School of Economics
United Kingdom
randomized computation
algorithms
sublinear algorithms
streaming algorithms
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Professor
Jon Kleinberg
Cornell University
Netherlands
algorithms
machine learning
algorithmic fairness
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Professor
Elad Hazan
Princeton University
United States of America
algorithms
machine learning
stochastic optimization
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Professor
Viswanath Nagarajan
University of Michigan
United States of America
algorithms
machine learning
stochastic optimization
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Professor
Sharan Vaswani
Simon Fraser University
Canada
algorithms
machine learning
stochastic optimization
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Professor
Yun Cheung
Australian National University
Australia
algorithms
machine learning
stochastic analysis
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Professor
Nicolas Loizou
Johns Hopkins University
United States of America
distributed decentralized algorithms
randomized numerical linear algebra
machine learning
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Professor
Danupon Na Nongkai
KTH Royal Institute of Technology
Sweden
approximation algorithms
quantum algorithms
data stream algorithms
graph algorithms
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Professor
Sigurd Assing
University of Warwick
United Kingdom
random processes
machine learning
stochastic analysis
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Professor
Eilyan Bitar
Cornell University
Netherlands
environment algorithms
machine learning
robust stochastic optimization
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Professor
Michał Dereziński
University of Michigan
United States of America
randomized numerical linear algebra
machine learning
stochastic optimization
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Professor
Longxiu Huang
Michigan State University
United States of America
random matrix analysis
random tensor analysis
machine learning
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Professor
Xiucai Ding
University of California, Davis
United States of America
randomized numerical linear algebra
applied random matrix theory
stochastic optimization
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Professor
Ivan Kryven
Utrecht University
Netherlands
randomized algorithms
random approximation algorithms
random matrices
random graph representation
stochastic analysis
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Professor
Debdeep Pati
University of Wisconsin–Madison
United States of America
fair algorithms
real-time tracking algorithms
machine learning
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Professor
Holger Hoos
RWTH Aachen University
Germany
automated machine learning
machine learning
automated reasoning
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Professor
Christian Schulz
Heidelberg University
Germany
algorithm engineering
machine learning
scalable graph algorithms
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