Abstract. This work addresses a class of total-variation based multilabeling problems over a spatially continuous image domain, where the data fidelity term can be any bounded fun...
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Projective Clustering Ensembles (PCE) are a very recent advance in data clustering research which combines the two powerful tools of clustering ensembles and projective clustering...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...
Submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including Max Cut in directed/undirected graphs and in hy...
Jon Lee, Vahab S. Mirrokni, Viswanath Nagarajan, M...
Nonlinear dimensionality reduction (NLDR) algorithms such as Isomap, LLE and Laplacian Eigenmaps address the problem of representing high-dimensional nonlinear data in terms of lo...