Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. ...
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
A wrapped feature selection process is proposed in the context of robust clustering based on Laplace mixture models. The clustering approach we consider is a generalization of the...
In this paper we propose a methodology for brain parcellation with anatomical and functional constraints dedicated to fMRI data analysis. The aim is to provide a representation of...
Graph drawing and visualization represent structural information ams of abstract graphs and networks. An important subset of graphs is directed acyclic graphs (DAGs). E-Spring alg...