The Restricted Isometry Property (RIP) is a concept used to characterize matrices that are nearly orthonormal when operating on sparse vectors. It is used in the field of compressed sensing and has been shown that random Gaussian, Bernoulli, and partial Fourier matrices satisfy the RIP with number of measurements nearly linear in the sparsity level. Computing these constants is strongly NP-hard.
UC Berkeley
Fall 2013
This course investigates the mathematical principles behind data and information analysis. It brings together concepts from statistics, optimization, and computer science, with a focus on large deviation inequalities, and convex analysis. It's tailored towards advanced graduate students who wish to incorporate these theories into their research.
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