We propose a variational bayes approach to the problem of robust estimation of gaussian mixtures from noisy input data. The proposed algorithm explicitly takes into account the un...
This paper proposes a set of novel multicast algorithms for m-D mesh overlay networks that can achieve shorter multicast delay and less resource consumptions. In contrast to previo...
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
This paper addresses the problem of fully automated
mining of public space video data. A novel Markov Clustering
Topic Model (MCTM) is introduced which builds on
existing Dynami...