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» A Tutorial on Spectral Clustering
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JMLR
2010
211views more  JMLR 2010»
14 years 5 months ago
Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
Bo Dai, Baogang Hu
107
Voted
ICANN
2001
Springer
15 years 3 months ago
Clustering of EEG-Segments Using Hierarchical Agglomerative Methods and Self-Organizing Maps
EEG segments recorded during microsleep events were transformed to the frequency domain and were subsequently clustered without the common summation of power densities in spectral ...
David Sommer, Martin Golz
89
Voted
NIPS
2007
15 years 16 days ago
DIFFRAC: a discriminative and flexible framework for clustering
We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The...
Francis Bach, Zaïd Harchaoui
IEICET
2010
92views more  IEICET 2010»
14 years 9 months ago
Spectral Methods for Thesaurus Construction
Traditionally, popular synonym acquisition methods are based on the distributional hypothesis, and a metric such as Jaccard coefficients is used to evaluate the similarity between...
Nobuyuki Shimizu, Masashi Sugiyama, Hiroshi Nakaga...
ISAAC
2007
Springer
109views Algorithms» more  ISAAC 2007»
15 years 5 months ago
Separating Populations with Wide Data: A Spectral Analysis
In this paper, we consider the problem of partitioning a small data sample drawn from a mixture of k product distributions. We are interested in the case that individual features a...
Avrim Blum, Amin Coja-Oghlan, Alan M. Frieze, Shuh...