Deviations of random matrices and applications
Introductory Workshop: phenomena in high dimensions August 21, 2017  August 25, 2017
Location: SLMath: Eisenbud Auditorium
Tags/Keywords
high dimensional probability
geometric functional analysis
convex sets
random projections
compressed sensing
16Vershynin
Uniform laws of large numbers provide theoretical foundations for statistical learning theory. This series of lectures will focus on quantitative uniform laws of large numbers for random matrices. A range of illustrations will be given in geometric functional analysis and data science, in particular to covariance estimation, signal recovery, and sparse regression.
16Vershynin
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