Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
This paper follows a word-document co-clustering model independently introduced in 2001 by several authors such as I.S. Dhillon, H. Zha and C. Ding. This model consists in creatin...
Submodular function minimization is a polynomially-solvable combinatorial problem. Unfortunately the best known general-purpose algorithms have high-order polynomial time complexi...
This paper presents a new object-based segmentation technique which exploits a large temporal context in order to get coherent and robust segmentation results. The segmentation pr...
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...