Abstract— We consider a convex unconstrained optimization problem that arises in a network of agents whose goal is to cooperatively optimize the sum of the individual agent objec...
Angelia Nedic, Alexander Olshevsky, Asuman E. Ozda...
—Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rat...
Michael Zargham, A. Ribeiro, Ali Jadbabaie, Asuman...
Multi-valued neurons are the neural processing elements with complex-valued weights, huge functionality (it is possible to implement on the single neuron arbitrary mapping describ...
Igor N. Aizenberg, Naum N. Aizenberg, Constantine ...
Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultaneously learning then the environment is no longer stationary, t...
In this paper, we show that the LVQ learning algorithm converges to locally asymptotic stable equilibria of an ordinary differential equation. We show that the learning algorithm ...