Abstract— Markets and auctions have been proposed as mechanisms for efficiently and fairly allocating resources in a number of different computational settings. Economic approac...
— Most existing work uses dual decomposition and subgradient methods to solve network optimization problems in a distributed manner, which suffer from slow convergence rate prope...
Ali Jadbabaie, Asuman E. Ozdaglar, Michael Zargham
In this paper we study the constrained consensus problem, i.e. the problem of reaching a common point from the estimates generated by multiple agents that are constrained to lie in...
Abstract— A distributed online learning framework for support vector machines (SVMs) is presented and analyzed. First, the generic binary classification problem is decomposed in...
The distributed estimation of the number of active sensors in a network can be important for estimation and organization purposes. We propose a design methodology based on the foll...