Given a unlabelled set of points X ∈ RN belonging to k groups, we propose a method to identify cluster assignments that provides maximum separating margin among the clusters. We...
The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
The work presented in this paper is an extension of our two previous works [1, 2]. In the first paper [1], we proposed a low dimensional feature (i-vectors) extractor which is su...
Mohammed Senoussaoui, Patrick Kenny, Pierre Dumouc...
The biclustering, co-clustering, or subspace clustering problem involves simultaneously grouping the rows and columns of a data matrix to uncover biclusters or sub-matrices of the...
Many image retargeting algorithms, despite aesthetically carving images smaller, pay limited attention to image browsing tasks where tiny thumbnails are presented. When applying t...