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ICANN
2007
Springer
15 years 4 months ago
Split-Merge Incremental LEarning (SMILE) of Mixture Models
In this article we present an incremental method for building a mixture model. Given the desired number of clusters K ≥ 2, we start with a two-component mixture and we optimize t...
Konstantinos Blekas, Isaac E. Lagaris
PKDD
2005
Springer
122views Data Mining» more  PKDD 2005»
15 years 3 months ago
A Probabilistic Clustering-Projection Model for Discrete Data
For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a ...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
ICPPW
2003
IEEE
15 years 3 months ago
Load Balancing on PC Clusters with the Super-Programming Model
Recent work in high-performance computing has shifted attention to PC clusters.. For PC-clusters, member nodes are independent computers connected by generalpurpose networks. The ...
Dejiang Jin, Sotirios G. Ziavras
ICPR
2010
IEEE
15 years 1 months ago
CDP Mixture Models for Data Clustering
—In Dirichlet process (DP) mixture models, the number of components is implicitly determined by the sampling parameters of Dirichlet process. However, this kind of models usually...
Yangfeng Ji, Tong Lin, Hongbin Zha
IJCAI
2007
14 years 11 months ago
Semantic Smoothing of Document Models for Agglomerative Clustering
In this paper, we argue that the agglomerative clustering with vector cosine similarity measure performs poorly due to two reasons. First, the nearest neighbors of a document belo...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu