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CVPR
2008
IEEE
16 years 9 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
KDD
2010
ACM
233views Data Mining» more  KDD 2010»
15 years 11 months ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
DATE
2005
IEEE
125views Hardware» more  DATE 2005»
16 years 25 days ago
Hybrid BIST Based on Repeating Sequences and Cluster Analysis
We present a hybrid BIST approach that extracts the most frequently occurring sequences from deterministic test patterns; these extracted sequences are stored on-chip. We use clus...
Lei Li, Krishnendu Chakrabarty
COLING
1996
15 years 8 months ago
An Automatic Clustering of Articles Using Dictionary Definitions
In this paper, we propose a statistical approach for clustering of artMes using on-line dictionary definitions. One of the characteristics of our approach is that every sense of w...
Fumiyo Fukumoto, Yoshimi Suzuki
TSE
2011
111views more  TSE 2011»
15 years 2 months ago
Software Module Clustering as a Multi-Objective Search Problem
Software module clustering is the problem of automatically organising software units into modules to improve program structure. There has been a great deal of recent interest in s...
Kata Praditwong, Mark Harman, Xin Yao