It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
Abstract. In this paper a new method for analyzing the intrinsic dimensionality (ID) of low dimensional manifolds in high dimensional feature spaces is presented. The basic idea is...
An efficient policy search algorithm should estimate the local gradient of the objective function, with respect to the policy parameters, from as few trials as possible. Whereas m...
Background: Predicting the subcellular localization of proteins is important for determining the function of proteins. Previous works focused on predicting protein localization in...
In this paper we introduce the idea of snapshot queries for energy efficient data acquisition in sensor networks. Network nodes generate models of their surrounding environment th...