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» Clustering with Local and Global Regularization
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NIPS
2001
13 years 9 months ago
Spectral Relaxation for K-means Clustering
The popular K-means clustering partitions a data set by minimizing a sum-of-squares cost function. A coordinate descend method is then used to nd local minima. In this paper we sh...
Hongyuan Zha, Xiaofeng He, Chris H. Q. Ding, Ming ...
ICASSP
2011
IEEE
12 years 11 months ago
Closed-form expressions vs. BIC: A comparison for speaker clustering
In this paper, the use of closed-form expressions is compared to the BIC approximation, with respect to speaker clustering. We first show that the particular BIC setting which is...
Themos Stafylakis, Xavier Anguera Miró, Vas...
BIBE
2007
IEEE
176views Bioinformatics» more  BIBE 2007»
14 years 2 months ago
HICCUP: Hierarchical Clustering Based Value Imputation using Heterogeneous Gene Expression Microarray Datasets
Abstract—A novel microarray value imputation method, HICCUP1 , is presented. HICCUP improves upon existing value imputation methods in the several ways. (1) By judiciously integr...
Qiankun Zhao, Prasenjit Mitra, Dongwon Lee, Jaewoo...
SISAP
2009
IEEE
159views Data Mining» more  SISAP 2009»
14 years 2 months ago
Dynamic P2P Indexing and Search Based on Compact Clustering
Abstract—We propose a strategy to perform query processing on P2P similarity search systems based on peers and superpeers. We show that by approximating global but resumed inform...
Mauricio Marín, Veronica Gil Costa, Cecilia...
ICDAR
2009
IEEE
14 years 2 months ago
Robust Recognition of Documents by Fusing Results of Word Clusters
The word error rate of any optical character recognition system (OCR) is usually substantially below its component or character error rate. This is especially true of Indic langua...
Venkat Rasagna, Anand Kumar 0002, C. V. Jawahar, R...