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AAAI
2004
15 years 7 months ago
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...
Zhihua Zhang, Kap Luk Chan, James T. Kwok, Dit-Yan...
ACL
2009
15 years 4 months ago
Bayesian Unsupervised Word Segmentation with Nested Pitman-Yor Language Modeling
In this paper, we propose a new Bayesian model for fully unsupervised word segmentation and an efficient blocked Gibbs sampler combined with dynamic programming for inference. Our...
Daichi Mochihashi, Takeshi Yamada, Naonori Ueda
ICASSP
2011
IEEE
14 years 10 months ago
Joint dictionary learning and topic modeling for image clustering
A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of th...
Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Cari...
WISE
2009
Springer
16 years 29 days ago
STC+ and NM-STC: Two Novel Online Results Clustering Methods for Web Searching
Results clustering in Web Searching is useful for providing users with overviews of the results and thus allowing them to restrict their focus to the desired parts. However, the ta...
Stella Kopidaki, Panagiotis Papadakos, Yannis Tzit...
BTW
2005
Springer
80views Database» more  BTW 2005»
15 years 11 months ago
Measuring the Quality of Approximated Clusterings
Abstract. Clustering has become an increasingly important task in modern application domains. In many areas, e.g. when clustering complex objects, in distributed clustering, or whe...
Hans-Peter Kriegel, Martin Pfeifle