On affinity matrix normalization for graph cuts and spectral clustering-Reference-Cited by-同舟云学术

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On affinity matrix normalization for graph cuts and spectral clustering

Published:2015-12 Issue: Volume:68 Page:90-96
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Beauchemin M.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference24 articles.

1. UCI Machine Learning Repository;Bache,2013

2. A density-based similarity matrix construction for spectral clustering;Beauchemin;Neurocomputing,2015

3. Spectral clustering: a semi-supervised approach;Chen;Neurocomputing,2012

4. Statistical comparisons of classifiers over multiple datasets;Demšar;J. Mach. Learn. Res.,2006

5. Weighted graph cuts without eigenvectors: a multilevel approach, IEEE Trans;Dhillon;Pattern Anal. Mach. Intell.,2007

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling;SIAM Journal on Mathematics of Data Science;2023-07-20

2. Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise;SIAM Journal on Mathematics of Data Science;2021-01

3. Sentence level matrix representation for document spectral clustering;Pattern Recognition Letters;2017-01

4. Automatic Scale Parameters in Affinity Matrix Construction for Improved Spectral Clustering;International Journal of Pattern Recognition and Artificial Intelligence;2016-11-23

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