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PR
2007
116views more  PR 2007»
15 years 6 months ago
GAPS: A clustering method using a new point symmetry-based distance measure
In this paper, an evolutionary clustering technique is described that uses a new point symmetry-based distance measure. The algorithm is therefore able to detect both convex and n...
Sanghamitra Bandyopadhyay, Sriparna Saha
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
177
Voted
ICCV
2011
IEEE
14 years 6 months ago
Source Constrained Clustering
We consider the problem of quantizing data generated from disparate sources, e.g. subjects performing actions with different styles, movies with particular genre bias, various con...
Ekaterina Taralova, Fernando DelaTorre, Martial He...
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