There is a number of recent research lines addressing complex negotiations in highly rugged utility spaces. However, most of them focus on overcoming the problems imposed by the c...
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...