Data Efficient Machine Learning Professors in Global

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Bartolomeo Stellato
Princeton University United States of America
machine learning
differentiable optimization
real-time embedded optimization
mathematical optimization
machine learning optimization data-driven algorithms
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Geoff Webb
Monash University Australia
machine learning
ensemble machine learning
interactive machine learning
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Morgane Austern
Harvard University United States of America
machine learning theory
learning structured data
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Yisong Yue
California Institute of Technology United States of America
machine learning
statistical machine learning
interactive machine learning
structured machine learning
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Yisong Yue
California Institute of Technology United States of America
statistical machine learning
interactive machine learning
structured machine learning
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Vatsa Patel
Penn State Harrisburg United States of America
machine learning
applied deep learning
data-driven modeling
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Yarin Gal
University of Oxford United Kingdom
machine learning
deep reinforcement learning
bayesian deep learning
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Yarin Gal
University of Oxford United Kingdom
machine learning
deep reinforcement learning
bayesian deep learning
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Muhammad Shafique
New York University Tandon School of Engineering United States of America
energy-efficient computing
embedded machine learning
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Gabriel Vigliensoni
Concordia University Canada
machine learning
interactive machine learning
creative machine learning
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Jens Pedersen
Technical University of Denmark Denmark
data processing
data extraction
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Axel Boisen
Technical University of Denmark Denmark
data processing
data extraction
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Dan Olteanu
University of Zurich Switzerland
data processing
in-database machine learning
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Panos Parpas
Imperial College London United Kingdom
computational optimization
mathematical optimization
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Andrei Shvarts
University of Glasgow United Kingdom
high-performance modelling
data-driven computational mechanics
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Martin Kada
Technical University of Berlin Germany
data analysis
data processing
spatial data modelling
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David Shmoys
Cornell University Netherlands
data-driven models
discrete optimization
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Qifan Song
Purdue University United States of America
machine learning
deep learning
massive data modeling
bayesian data science
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Steven Reece
University of Oxford United Kingdom
machine learning
interpretable machine learning
bayesian deep learning
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Marina Epelman
University of Michigan United States of America
discrete optimization
mathematical optimization
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Mark Daskin
University of Michigan United States of America
discrete optimization
mathematical optimization
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