Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
A large number of problems in computer vision can be modeled as energy minimization problems in a markov random field (MRF) framework. Many methods have been developed over the y...
Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...
DNA copy number variants (CNV) are gains and losses of segments of chromosomes, and comprise an important class of genetic variation. Recently, various microarray hybridization ba...
Predicting and proper ranking of splice sites (SS) is a challenging problem in bioinformatics and machine learning communities. Proposed method of donor and acceptor SSs predictio...