This paper proposes a new class of simple, distributed algorithms for scheduling in wireless networks. The algorithms generate new schedules in a distributed manner via simple loc...
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
Collaborative signal processing is one of the most promising applications that are currently being investigated for sensor networks. In this paper, we use FFT computation as a veh...
We present a framework for constructing representations of space in an autonomous agent which does not obtain any direct information about its location. Instead the algorithm relie...
This paper presents two methods for improving the performance of the Distributed Breakout Algorithm using the notion of interchangeability. In particular, we use neighborhood part...