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» Spectral clustering based on matrix perturbation theory
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DIS
2006
Springer
13 years 11 months ago
Clustering Pairwise Distances with Missing Data: Maximum Cuts Versus Normalized Cuts
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
Jan Poland, Thomas Zeugmann
PAMI
2010
192views more  PAMI 2010»
13 years 5 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens
COLT
2010
Springer
13 years 5 months ago
Learning Rotations with Little Regret
We describe online algorithms for learning a rotation from pairs of unit vectors in Rn . We show that the expected regret of our online algorithm compared to the best fixed rotati...
Elad Hazan, Satyen Kale, Manfred K. Warmuth
ICIP
2004
IEEE
14 years 9 months ago
Robust perceptual image hashing via matrix invariants
In this paper we suggest viewing images (as well as attacks on them) as a sequence of linear operators and propose novel hashing algorithms employing transforms that are based on ...
Mehmet Kivanç Mihçak, Ramarathnam Ve...
ISBI
2011
IEEE
12 years 11 months ago
Sparse Riemannian manifold clustering for HARDI segmentation
We address the problem of segmenting high angular resolution diffusion images of the brain into cerebral regions corresponding to distinct white matter fiber bundles. We cast thi...
Hasan Ertan Çetingül, René Vida...