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IPMI
2009
Springer
14 years 8 months ago
Tractography Segmentation Using a Hierarchical Dirichlet Processes Mixture Model
In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. Th...
Carl-Fredrik Westin, W. Eric L. Grimson, Xiaogang ...
NPL
2000
88views more  NPL 2000»
13 years 7 months ago
Learning Synaptic Clusters for Nonlinear Dendritic Processing
Nonlinear dendritic processing appears to be a feature of biological neurons and would also be of use in many applications of artificial neural networks. This paper presents a mod...
Michael W. Spratling, Gillian Hayes
ICONIP
2008
13 years 8 months ago
Local Feature Selection in Text Clustering
Abstract. Feature selection has improved the performance of text clustering. Global feature selection tries to identify a single subset of features which are relevant to all cluste...
Marcelo N. Ribeiro, Manoel J. R. Neto, Ricardo Bas...
ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
14 years 1 months ago
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
ICASSP
2009
IEEE
14 years 2 months ago
Bandwidth adaptive hardware architecture of K-Means clustering for intelligent video processing
K-Means is a clustering algorithm that is widely applied in many elds, including pattern classi cation and multimedia analysis. Due to real-time requirements and computational-cos...
Tse-Wei Chen, Shao-Yi Chien