This paper presents a new framework for blind source separation (BSS) of non-negative source signals. The proposed framework, referred herein to as convex analysis of mixtures of ...
We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
Most current work in data mining assumes that the database is static, and a database update requires rediscovering all the patterns by scanning the entire old and new database. Su...
Abstract. This paper is concerned with the reliable inference of optimal treeapproximations to the dependency structure of an unknown distribution generating data. The traditional ...
Background: Statistical comparison of peptide profiles in biomarker discovery requires fast, userfriendly software for high throughput data analysis. Important features are flexib...
Mark K. Titulaer, Ivar Siccama, Lennard J. Dekker,...