Matrix Factorization Professors in Global

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Andersen Ang
University of Southampton United Kingdom
nonnegative matrix factorization
mathematical programming
machine learning
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Paul Mcnicholas
McMaster University Canada
matrix variate distributions
pattern recognition
machine learning
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Yiran Liu
University of Western Australia Australia
machine learning
optimisation
modelling
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David Scheinker
Stanford University United States of America
mathematical optimization
machine learning
probabilistic modeling
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Manuel Lopez-ibanez
University of Manchester United Kingdom
machine learning
optimisation
combinatorial optimisation
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John Urschel
Massachusetts Institute of Technology United States of America
matrix analysis
matrix computations
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Jacek Gondzio
University of Edinburgh United Kingdom
sparse matrix factorization
linear programming
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François Glineur
Catholic University of Louvain Belgium
nonnegative matrix factorization
mathematical optimization
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Shaun Fallat
University of Regina Canada
matrix theory
combinatorial matrix analysis
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Anshul Thakur
University of Oxford United Kingdom
tensor factorization
machine learning
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Ralf Zimmermann
University of Southern Denmark Denmark
matrix analysis
mathematical modelling
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Andrii Dmytryshyn
University of Gothenburg Sweden
matrix theory
polynomial matrices
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Luis Rademacher
University of California, Davis United States of America
matrix computations
machine learning
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Nate Veldt
Texas A&M University United States of America
matrix computations
machine learning
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Alexey Onatskiy
University of Cambridge United Kingdom
factor models
large random matrices
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Leili Rafiee Sevyeri
University of Waterloo Canada
matrix polynomials
algebraic linearizations
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Andrew Oates
École Polytechnique Fédérale de Lausanne Switzerland
mathematical modelling
patterning
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Holger Rauhut
Ludwig-Maximilians-Universität München Germany
random matrices
machine learning
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Babak Hassibi
California Institute of Technology United States of America
random matrices
machine learning
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Katta Murty
University of Michigan United States of America
math modeling
math programming
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Babak Hassibi
California Institute of Technology United States of America
random matrices
machine learning
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