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CDC
2008
IEEE
147views Control Systems» more  CDC 2008»
14 years 2 months ago
Clustering neural spike trains with transient responses
— The detection of transient responses, i.e. non– stationarities, that arise in a varying and small fraction of the total number of neural spike trains recorded from chronicall...
John D. Hunter, Jianhong Wu, John G. Milton
KDD
2005
ACM
119views Data Mining» more  KDD 2005»
14 years 1 months ago
LIPED: HMM-based life profiles for adaptive event detection
In this paper, the proposed LIPED (LIfe Profile based Event Detection) employs the concept of life profiles to predict the activeness of event for effective event detection. A gro...
Chien Chin Chen, Meng Chang Chen, Ming-Syan Chen
GBRPR
2007
Springer
13 years 11 months ago
Constellations and the Unsupervised Learning of Graphs
Abstract. In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an E...
Boyan Bonev, Francisco Escolano, Miguel Angel Loza...
CIMCA
2005
IEEE
14 years 1 months ago
Modeling the Cross-Cultural Adaptation Process of Immigrants Using Categorical Data Clustering
— This paper introduces a quantitative method for social data analysis, which is based on the use of categorical data clustering. More specifically, we employ categorical data cl...
George E. Tsekouras
ICDM
2003
IEEE
111views Data Mining» more  ICDM 2003»
14 years 1 months ago
OP-Cluster: Clustering by Tendency in High Dimensional Space
Clustering is the process of grouping a set of objects into classes of similar objects. Because of unknownness of the hidden patterns in the data sets, the definition of similari...
Jinze Liu, Wei Wang 0010