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ICML
2010
IEEE
15 years 4 months ago
Comparing Clusterings in Space
This paper proposes a new method for comparing clusterings both partitionally and geometrically. Our approach is motivated by the following observation: the vast majority of previ...
Michael H. Coen, M. Hidayath Ansari, Nathanael Fil...
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
15 years 4 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu
CSDA
2010
133views more  CSDA 2010»
15 years 4 months ago
Optimized fixed-size kernel models for large data sets
A modified active subset selection method based on quadratic R
Kris De Brabanter, Jos De Brabanter, Johan A. K. S...
ICDM
2008
IEEE
122views Data Mining» more  ICDM 2008»
16 years 1 months ago
Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding
Nonnegative matrix factorization (NMF) is a versatile model for data clustering. In this paper, we propose several NMF inspired algorithms to solve different data mining problems....
Chris H. Q. Ding, Tao Li, Michael I. Jordan
CIBCB
2005
IEEE
16 years 13 days ago
Functional Distances for Genes Based on GO Feature Maps and their Application to Clustering
— With the invention of high throughput methods, researchers are capable of producing large amounts of biological data. During the analysis of such data, the need for a functiona...
Nora Speer, Holger Fröhlich, Christian Spieth...