Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
A methodology for automatically identifying and clustering semantic features or topics in a heterogeneous text collection is presented. Textual data is encoded using a low rank no...
Farial Shahnaz, Michael W. Berry, V. Paul Pauca, R...
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. The problem often is multi-modal and therefore appropriate optimi...
Christian Spieth, Felix Streichert, Nora Speer, An...
In this paper, an extension of a dimensionality reduction algorithm called NONNEGATIVE MATRIX FACTORIZATION is presented that combines both `bag of words' data and syntactic ...
Abstract. Competitive learning approaches with penalization or cooperation mechanism have been applied to unsupervised data clustering due to their attractive ability of automatic ...