Sparse Sampling Professors in Global

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Trac-duy Tran
Johns Hopkins University United States of America
sparse representation
sampling
sparse recovery
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Giang Tran
University of Waterloo Canada
sparse modeling
sparse optimization methods
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Ian Wassell
University of Cambridge United Kingdom
sparse representation data
sparse image video coding
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Steven Brunton
University of Washington United States of America
sparse sensing
optimal placement of sparse sensors and actuators
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Daniel Xiang
University of Chicago United States of America
sparse-approximation signal detection
selective inference
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Mark Handcock
University of California Los Angeles United States of America
survey sampling
stochastic modeling
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Mahdi Cheraghchi
Imperial College London United Kingdom
sparse recovery
randomized computation
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Ivan Kryven
Utrecht University Netherlands
spectral properties of sparse graphs
stochastic analysis
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John Lau
University of Western Australia Australia
statistical filtering
statistical clustering
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Nazim Khan
University of Western Australia Australia
stochastic modelling
statistical clustering
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P. Vaidyanathan
California Institute of Technology United States of America
sparse sampling
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Joel Tropp
California Institute of Technology United States of America
sparse modeling
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Alper Atamturk
University of California, Berkeley United States of America
sparse learning
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Vassilis Digalakis
Boston University United States of America
sparse machine learning
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Anica Kostic
London School of Economics United Kingdom
sparse modelling
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Guillaume Obozinski
École Polytechnique Fédérale de Lausanne Switzerland
sparse modeling
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Irina Rish
University of Montreal Canada
sparse modeling
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Aydin Buluç
University of California, Berkeley United States of America
sparse computations
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Line Clemmensen
Technical University of Denmark Denmark
sparse methods
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Bernard Baffour
Australian National University Australia
sparse data
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Juan Vera Lizcano
Tilburg University Netherlands
sparse methods
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