CBMS Conference: Sparse Approximation and Signal Recovery Algorithms

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This grant provides support for the CBMS Conference on Sparse Approximation and Signal Recovery Algorithms, which will take place at New Mexico State University, Las Cruces on May 22-26, 2017. Professor Anna C. Gilbert of the University of Michigan will provide a lecture series on Sparse Approximation and Signal Recovery Algorithms. The subject matter lies at the interface of applied mathematics, electrical and computer engineering, and information science. The subject is chosen to build and strengthen existing research ties between the host institution and other institutions and technical industries in the Southwest region. A primary goal is to bring a large group of researchers in mathematics and applications to the cutting edge of sparse approximation techniques and applications. Sparse approximation problems arise in a variety of applications concerning digital communications and analysis of large datasets. The lecture series will begin with basic mathematical formulations of sparse approximation and signal recovery problems. It will proceed with a discussion of greedy algorithms and convex methods, such as basis pursuit, sublinear algorithms for streaming and sketching, and Fourier sampling methods. The lectures will conclude outlining specific applications such as GPS synchronization, spectrum sensing, and correlation spectroscopy. The principal lecturer Anna C. Gilbert is the Herman H. Goldstine Collegiate Professor of Mathematics at the University of Michigan. She is the recipient of numerous prestigious awards, including the SIAM Ralph E. Kleinman Prize for outstanding contributions that bridge mathematics and applications. Further details, including plans to fund participant travel and registration information, can be found at: https://www.math.nmsu.edu/activities/cbms2017/cbms2017.html