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PR
2007
189views more  PR 2007»
13 years 7 months ago
Information cut for clustering using a gradient descent approach
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...
CIBCB
2005
IEEE
14 years 1 months ago
Functional Distances for Genes Based on GO Feature Maps and their Application to Clustering
— 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...
Nora Speer, Holger Fröhlich, Christian Spieth...
CSDA
2007
99views more  CSDA 2007»
13 years 7 months ago
CLUES: A non-parametric clustering method based on local shrinking
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 ...
Xiaogang Wang, Weiliang Qiu, Ruben H. Zamar
ICML
2004
IEEE
14 years 8 months ago
Boosting margin based distance functions for clustering
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...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
VTC
2006
IEEE
129views Communications» more  VTC 2006»
14 years 1 months ago
A Framework for Automatic Clustering of Parametric MIMO Channel Data Including Path Powers
— 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...