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Abstract: The normalized cut (NC) provides a plausible cost function for clustering. Finding an optimal NC is NP-hard, and the well-known spectral graph partition methods rely on a loose spectral relaxation. (Update)
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1.4: On Semidefinite Relaxations for Normalized k-Cut and.. - Xing, Jordan (2003) (Correct)
1.4: Unknown - (Correct)
0.3: Learning Spectral Clustering - Bach, Jordan (2003) (Correct)
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BibTeX entry: (Update)
@misc{ -unknown,
title = "Unknown",
url = "citeseer.ist.psu.edu/736629.html" }
Citations (may not include all citations):415 Improved approximation algorithms for maximum cut and satis .. - Goemans, Williamson - 1995
193 Normalized cuts and image segmentation - Shi, Malik - 2000
112 Improved approximation algorithms for MAX k-CUT and MAX BISE.. - Frieze, Jerrum - 1995
93 American Mathematical Society (context) - Chung, Theory et al. - 1997
81 a MATLAB toolbox for optimization over symmetric cones (context) - Sturm - 1999
72 On spectral clustering: Analysis and an algorithm - Ng, Jordan et al. - 2002
38 Semide nite programming (context) - Vandenberghe, Boyd - 1996
36 bad and spectral (context) - Kannan, Vempala et al. - 2001
23 with application to clustering with side-information (context) - Xing, Ng et al. - 2002
20 the sum of the largest eigenvalues of a symmetric matrix (context) - Overton, Womersley - 1992
10 Learning spectral clustering - Bach, Jordan - 2003
10 the quality of spectral separators - Guattery, Miller - 1998
8 A random walks view of spectral segmentation (context) - Maila, Shi - 2001
7 Spectral relaxation models and structure analysis for k-way .. - Gu, Zha et al. - 2001
6 Clustering of high-dimensional microarray data via iterative.. (context) - Xing, Karp - 2001
4 Semide nite programming and graph equipartition (context) - Karisch, Rendl - 1998
3 Concurrent object segmentation and recognition with graph pa.. (context) - Yu, Gross et al. - 2002
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