We propose a novel strategy for training neural networks using sequential Monte Carlo algorithms. This global optimisation strategy allows us to learn the probability distribution...
—In a sensor network, data routing is tightly coupled to the needs of a sensing task, and hence the application semantics. This paper introduces the novel idea of information-dir...
We consider principal component analysis (PCA) in decomposable Gaussian graphical models. We exploit the prior information in these models in order to distribute its computation. ...
A distributed set-membership-constrained particle filter (SMCPF) is developed for decentralized tracking applications using wireless sensor networks. Unlike existing PF alternati...
Shahrokh Farahmand, Stergios I. Roumeliotis, Georg...
In this work we present a parallel algorithm for the solution of a least squares problem with structured matrices. This problem arises in many applications mainly related to digit...
Pedro Alonso, Antonio M. Vidal, Alexey L. Lastovet...