The mutual information is a core statistical quantity that has applications in all areas of
machine learning, whether this is in training of density models over multiple data modalities …

We study the use of replicator dynamics for data clustering and structure identification. We
investigate that replicator dynamics, while running, reveals informative transitions that …

Truncated Singular Value Decomposition (SVD) calculates the closest rank-k approximation
of a given input matrix. Selecting the appropriate rank k defines a critical model order choice …

The goal of model-order selection is to select a model variant that generalizes best from
training data to unseen test data. In unsupervised learning without any labels, the …

Sorting is a data structure operation involving a re-arrangement of an unordered set of
elements with witnessed real life applications for load balancing and energy conservation in …

A theory of patterns analysis has to suggest criteria how patterns in data can be defined in a
meaningful way and how they should be compared. Similarity-based Pattern Analysis and …

This thesis focuses on an information-theoretic analysis of clustering algorithms. In many
real-world applications, because of imprecise or incomplete measurements, the data is …

We organized a data mining challenge in “unsupervised and transfer learning”(the UTL
challenge) followed by a workshop of the same name at the ICML 2011 conference in …

One of the most promising avenues for compiling connectivity data originates from the notion
that individual brain regions maintain individual connectivity profiles; the functional …

Structural connectivity plays a dominant role in brain function and arguably lies at the core of
understanding the structure-function relationship in the cerebral cortex. Connectivity-based …