Roman Vershynin | Slides of presentations

• Analysis of random measurements. Short Course "Sparse Representations and High Dimensional Geometry", IPAM, UCLA, Los Angeles, CA, 2007

  Lecture 1: The Sparse reconstruction problem and random matrices

  Lecture 2: Upper and lower bounds for subgaussian matrices

  Lecture 3: Random Fourier matrices

  Commentary and Bibliography

• Uncertainty principles, frames, and quantization. Trends in Harmonic Analysis, Strobl, Austria, 2007.
• Anti-concentration inequalities. Phenomena in High Dimensions, Samos, Greece, 2007.
• Sparse representations and invertibility of random matrices, AMS 2007 Von Neumann Symposium, Snowbird, Utah, 2007
• Compressed Sensing. Applied Mathematics Seminar, UC Davis, 2007
• Small ball probability, additive structure and random matrices, DIMACS, Rutgers University, 2008
• On the role of sparsity in compressed sensing and random matrix theory, CAMSAP 09, Aruba, 2009
• Random matrix theory from the functional analytic perspective, SEAM XXVI, Georgia Tech, Atlanta, 2010
• Estimation of covariance matrices, Probability and Geometry in High Dimensions, Paris, France, 2010. A slightly modified version (with a discussion of Levy flights) is in my talk at UM Statistics.
• Non-asymptotic theory of random matrices and sparsity, Bonn Mathematical Colloquium and Workshop on Sparsity and Computation, Bonn, Germany, 2010
• Non-asymptotic theory of random matrices: extreme singular values, International Congress of Mathematicians, Hyderabad, India, 2010
• Covariance estimation and invertibility of random matrices, joint PACM Colloquium and Analysis Seminar, Princeton, 2011. A slightly edited version is a talk at MSU.
• Random matrices: invertibility, structure, and applications, Canadian Mathematical Society Summer Meeting, Edmonton, Alberta, 2011.
• 9-hour course on non-asymptotic analysis of random matrices, Summer School on Random matrices - stochastic geometry - compressed sensing, Institut Henri Poincare, France, 2011.
• Invertibility of symmetric random matrices, Random Matrices, Bonn, Germany, 2012.
• New ways of dimension reduction? Cutting data sets into small pieces, Statistical Learning and Data Mining, Ann Arbor, 2012.
• Random hyperplane tessellations and dimension reduction, Phenomena in high dimensions in geometric analysis, random matrices and computational geometry, Roscoff, France, 2012.
• Probabilistic reasoning in compresses sensing, Journees MAS, Clermont-Ferrand, France, 2012.