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Granular-ball computing-based manifold clustering algorithms for ultra-scalable data

  • Published:2024-08 Issue: Volume:247 Page:123313
  • ISSN:0957-4174
  • Container-title:Expert Systems with Applications
  • language:en
  • Short-container-title:Expert Systems with Applications

Author:

Cheng DongdongORCID,Liu ShushuORCID,Xia Shuyin,Wang GuoyinORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Chongqing Municipality

Chongqing Municipal Education Commission

National Postdoctoral Program for Innovative Talents

Publisher

Elsevier BV

Reference44 articles.

1. Cumulative voting consensus method for partitions with variable number of clusters;Ayad;IEEE Transactions on Pattern Analysis and Machine Intelligence,2008

2. Laplacian eigenmaps and spectral techniques for embedding and clustering;Belkin;Advances in Neural Information Processing Systems,2002

3. Salient object detection: A benchmark;Borji;IEEE Transactions on Image Processing,2015

4. Large scale spectral clustering via landmark-based sparse representation;Cai;IEEE Transactions on Cybernetics,2015

5. Cai, D., He, X., & Han, J. (2007). Spectral regression: A unified subspace learning framework for content-based image retrieval. In Proceedings of the 15th ACM international conference on multimedia (pp. 403–412).

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1. Purity Skeleton Dynamic Hypergraph Neural Network;Neurocomputing;2024-12

2. Density-based clustering with differential privacy;Information Sciences;2024-10

3. Granular Ball Twin Support Vector Machine With Pinball Loss Function;IEEE Transactions on Computational Social Systems;2024
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