Spectral Clustering of Large-scale Data by Directly Solving Normalized Cut
Author:
Affiliation:
1. Shenzhen University, Shenzhen, China
2. Northwestern Polytechnical University, Xi'an, China
3. Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, Shenzhen, China
Funder
National Natural Science Foundation of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3219819.3220039
Reference21 articles.
1. Large Scale Spectral Clustering Via Landmark-Based Sparse Representation
2. Heterogeneous image feature integration via multi-modal spectral clustering
3. Xiaojun Chen Joshua Zhexue Huang Feiping Nie Renjie Chen and Qingyao Wu . 2017 a. A Self-Balanced Min-Cut Algorithm for Image Clustering Proceedings of the International Conference on Computer Vision ICCV-17. 2080--2088. Xiaojun Chen Joshua Zhexue Huang Feiping Nie Renjie Chen and Qingyao Wu . 2017 a. A Self-Balanced Min-Cut Algorithm for Image Clustering Proceedings of the International Conference on Computer Vision ICCV-17. 2080--2088.
4. TW-k-means: Automated two-level variable weighting clustering algorithm for multiview data
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