In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
We propose a new approach to value-directed belief state approximationfor POMDPs. The valuedirected model allows one to choose approximation methods for belief state monitoringtha...
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
We propose a new data structure to search in metric spaces. A metric space is formed by a collection of objects and a distance function de ned among them, which satis es the trian...
Abstract. Connected dominating set (CDS) has a wide range of applications in wireless ad hoc networks. A number of approximation algorithms for constructing a small CDS in wireless...