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Abstract: Many problems in science and engineering ask for solutions to underdetermined systems of linear equations. The last decade has witnessed a flurry of activity in understanding when and how it is possible to solve such problems using convex programming. Structured signal recovery via convex methods has arguably revolutionized signal acquisition, enabling signals to be measured with remarkable fidelity using a small number of measurements. In this talk I will argue that the over insistence on convex methods has stymied progress in this field. I will review my past and ongoing research efforts to “unshackle” structured signal recovery from the confines of convexity opening the door for new applications. This is based on joint work with collaborators who shall be properly introduced during the talk.

Bio: Dr. Soltanolkotabi obtained his B.S. in electrical engineering at Sharif University of Technology, Tehran, Iran in 2009. He completed his M.S. and Ph.D. in electrical engineering at Stanford University in 2011 and 2014, respectively, under the supervision of Emmanuel Candes. He was a postdoctoral researcher in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley from August 2014 - August 2015. He joined the EE Department at USC in 2015 as an assistant professor.

structured_signal_recovery_without_the_shackles_of_convexity.txt · Last modified: 2016/09/01 19:15 (external edit)