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NIPS
2004
13 years 6 months ago
A Probabilistic Model for Online Document Clustering with Application to Novelty Detection
In this paper we propose a probabilistic model for online document clustering. We use non-parametric Dirichlet process prior to model the growing number of clusters, and use a pri...
Jian Zhang 0003, Zoubin Ghahramani, Yiming Yang
WWW
2008
ACM
13 years 4 months ago
A Novelty-based Clustering Method for On-line Documents
In this paper, we describe a document clustering method called noveltybased document clustering. This method clusters documents based on similarity and novelty. The method assigns...
Sophoin Khy, Yoshiharu Ishikawa, Hiroyuki Kitagawa
NIPS
2001
13 years 6 months ago
Model Based Population Tracking and Automatic Detection of Distribution Changes
Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
Igor V. Cadez, Paul S. Bradley
AAAI
2010
13 years 2 months ago
A Topic Model for Linked Documents and Update Rules for its Estimation
The latent topic model plays an important role in the unsupervised learning from a corpus, which provides a probabilistic interpretation of the corpus in terms of the latent topic...
Zhen Guo, Shenghuo Zhu, Zhongfei Zhang, Yun Chi, Y...
PAMI
2007
166views more  PAMI 2007»
13 years 4 months ago
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
—This paper presents a novel probabilistic approach to hierarchical, exemplar-based shape matching. No feature correspondence is needed among exemplars, just a suitable pairwise ...
Dariu Gavrila