In the last decade, Social Network Analysis has been a field in which the effort devoted from several researchers in the Data Mining area has increased very fast. Among the possibl...
We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory net...
Abstract. This paper presents a novel technique for separating convolutive mixtures of statistically independent non-Gaussian signals. The time-domain convolution is transformed in...
Searching for interesting patterns in binary matrices plays an important role in data mining and, in particular, in formal concept analysis and related disciplines. Several algorit...
Abstract. We present a new algorithm for approximate joint diagonalization of several symmetric matrices. While it is based on the classical least squares criterion, a novel intrin...
We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of co...
Knowledge extraction from data volumes of ever increasing size requires ever more flexible tools to facilitate interactive query. Interactivity enables real-time hypothesis testin...
Kenny Gruchalla, Mark Rast, Elizabeth Bradley, Joh...
Although k-means clustering is often applied to time series clustering, the underlying Euclidean distance measure is very restrictive in comparison to the human perception of time ...