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PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 8 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
CSDA
2006
98views more  CSDA 2006»
15 years 4 months ago
Fast estimation algorithm for likelihood-based analysis of repeated categorical responses
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...
Jukka Jokinen
BMCBI
2010
171views more  BMCBI 2010»
15 years 4 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
MICRO
2002
IEEE
143views Hardware» more  MICRO 2002»
15 years 9 months ago
Effective instruction scheduling techniques for an interleaved cache clustered VLIW processor
Clustering is a common technique to overcome the wire delay problem incurred by the evolution of technology. Fully-distributed architectures, where the register file, the functio...
Enric Gibert, F. Jesús Sánchez, Anto...
AAAI
2008
15 years 6 months ago
Clustering via Random Walk Hitting Time on Directed Graphs
In this paper, we present a general data clustering algorithm which is based on the asymmetric pairwise measure of Markov random walk hitting time on directed graphs. Unlike tradi...
Mo Chen, Jianzhuang Liu, Xiaoou Tang