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» Consistent Minimization of Clustering Objective Functions
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87
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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
15 years 10 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
75
Voted
AAAI
2007
14 years 12 months ago
Clustering with Local and Global Regularization
Clustering is an old research topic in data mining and machine learning communities. Most of the traditional clustering methods can be categorized local or global ones. In this pa...
Fei Wang, Changshui Zhang, Tao Li
ICDM
2007
IEEE
139views Data Mining» more  ICDM 2007»
15 years 3 months ago
Data Clustering with a Relational Push-Pull Model
We present a new generative model for relational data in which relations between objects can have either a binding or a separating effect. For example, in a group of students sep...
Adam Anthony, Marie desJardins
ASPDAC
1999
ACM
122views Hardware» more  ASPDAC 1999»
15 years 1 months ago
A Clustering Based Linear Ordering Algorithm for K-Way Spectral Partitioning
The spectral method can lead to a high quality of multi-way partition due to its ability to capture global netlist information. For spectral partition, n netlist modules are mappe...
Shiuann-Shiuh Lin, Wen-Hsin Chen, Wen-Wei Lin, Tin...
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
15 years 10 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis