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AAIM
2009
Springer
118views Algorithms» more  AAIM 2009»
16 years 24 days ago
A More Relaxed Model for Graph-Based Data Clustering: s-Plex Editing
We introduce the s-Plex Editing problem generalizing the well-studied Cluster Editing problem, both being NP-hard and both being motivated by graph-based data clustering. Instead o...
Jiong Guo, Christian Komusiewicz, Rolf Niedermeier...
NIPS
2004
15 years 7 months ago
Spike Sorting: Bayesian Clustering of Non-Stationary Data
Spike sorting involves clustering spike trains recorded by a microelectrode according to the source neuron. It is a complicated problem, which requires a lot of human labor, partl...
Aharon Bar-Hillel, Adam Spiro, Eran Stark
EUROPAR
1999
Springer
15 years 10 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene
KDD
2003
ACM
210views Data Mining» more  KDD 2003»
16 years 6 months ago
Privacy-preserving k-means clustering over vertically partitioned data
Privacy and security concerns can prevent sharing of data, derailing data mining projects. Distributed knowledge discovery, if done correctly, can alleviate this problem. The key ...
Jaideep Vaidya, Chris Clifton
BIBM
2008
IEEE
101views Bioinformatics» more  BIBM 2008»
16 years 20 days ago
Comparing and Clustering Flow Cytometry Data
Flow cytometry technique produces large, multidimensional datasets of properties of individual cells that are helpful for biomedical science and clinical research. This paper expl...
Lin Liu, Li Xiong, James J. Lu, Kim M. Gernert, Vi...