A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints
In this paper we present a variant of random coordinate descent method for solving linearly constrained convex optimization problems with composite objective function. If the smooth part has Lipschitz continuous gradient, then the method terminates with an ϵ-optimal solution in O(N2/ϵ) iterations, where N is the number of blocks. For the class of problems with … Read more