In this talk we will discuss low-complexity algorithms for solving large-scale convex optimization problems. Such algorithms include: gradient projection, proximal gradient, Iterative Shrinkage-Thresholding (ISTA), Nesterov's acceleration, and Alternating Direction Method of Multipliers (ADMM). The emphasis of the discussion will be placed on th...
Zhang, Shuzhong (University of Minnesota, Twin Cities)
University of Minnesota, Institute for Mathematics and its Applications.