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» Bayesian Feedback in Data Clustering
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IJCAI
2007
13 years 8 months ago
Collapsed Variational Dirichlet Process Mixture Models
Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
Kenichi Kurihara, Max Welling, Yee Whye Teh
CVPR
2008
IEEE
14 years 9 months ago
Simultaneous clustering and tracking unknown number of objects
In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...
Katsuhiko Ishiguro, Takeshi Yamada, Naonori Ueda
SDM
2007
SIAM
184views Data Mining» more  SDM 2007»
13 years 8 months ago
Mining Naturally Smooth Evolution of Clusters from Dynamic Data
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
Yi Wang, Shi-Xia Liu, Jianhua Feng, Lizhu Zhou
CIKM
2008
Springer
13 years 9 months ago
Active relevance feedback for difficult queries
Relevance feedback has been demonstrated to be an effective strategy for improving retrieval accuracy. The existing relevance feedback algorithms based on language models and vect...
Zuobing Xu, Ram Akella
CLASSIFICATION
2006
108views more  CLASSIFICATION 2006»
13 years 7 months ago
The Practice of Cluster Analysis
Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
Jon R. Kettenring