We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between p...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
— With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data, the need for a functiona...
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
— We present a solution to the problem of identifying clusters from MIMO measurement data in a data window, with a minimum of user interaction. Conventionally, visual inspection ...
Nicolai Czink, Pierluigi Cera, Jari Salo, Ernst Bo...