Distributed Projection on the Simplex and l1 Ball via ADMM and Gossip
Abstract
We derive distributed algorithms for projecting the local values of the agents of a computing network on the simplex or on the ℓ1 -ball. These algorithms are based on distributed ADMM to solve a convex optimization problem of the form minx∑nfn(x) , where each function fn is local to node n and has an easy-to-compute proximity operator.