We study the problem of load balancing the traffic from a set of unicast and multicast sessions. The problem is formulated as an optimization problem. However, we assume that the g...
—We apply large deviations theory to study asymptotic performance of running consensus distributed detection in sensor networks. Running consensus is a stochastic approximation t...
Abstract. In this paper we study distributed online learning of locomotion gaits for modular robots. The learning is based on a stochastic approximation method, SPSA, which optimiz...
—In this paper, recent results in game theory and stochastic approximation are brought together to mitigate the problem of femto-to-macrocell cross-tier interference. The main re...
Abstract— In this paper, we propose a power optimal opportunistic scheduling scheme for a multiuser single hop Time Division Multiple Access (TDMA) system. We formulate the probl...
Abhijeet Bhorkar, Abhay Karandikar, Vivek S. Borka...