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» Boosting margin based distance functions for clustering
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UAI
2004
13 years 10 months ago
Similarity-Driven Cluster Merging Method for Unsupervised Fuzzy Clustering
In this paper, a similarity-driven cluster merging method is proposed for unsupervised fuzzy clustering. The cluster merging method is used to resolve the problem of cluster valid...
Xuejian Xiong, Kap Luk Chan
ESWA
2008
119views more  ESWA 2008»
13 years 8 months ago
Incremental clustering of mixed data based on distance hierarchy
Clustering is an important function in data mining. Its typical application includes the analysis of consumer's materials. Adaptive resonance theory network (ART) is very pop...
Chung-Chian Hsu, Yan-Ping Huang
ECCV
2010
Springer
14 years 1 months ago
Robust Multi-View Boosting with Priors
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
ICML
2004
IEEE
14 years 9 months ago
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
RIAO
2007
13 years 10 months ago
Similarity Beyond Distance Measurement
One of the keys issues to content-based image retrieval is the similarity measurement of images. Images are represented as points in the space of low-level visual features and mos...
Feng Kang, Rong Jin, Steven C. H. Hoi