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Semi-supervised feature selection analysis with structured multi-view sparse regularization.

, , , , , and . Neurocomputing, (2019)

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Individuality Meets Commonality: A Unified Graph Learning Framework for Multi-View Clustering., and . ACM Trans. Knowl. Discov. Data, 17 (1): 7:1-7:21 (January 2023)Semi-supervised feature selection analysis with structured multi-view sparse regularization., , , , , and . Neurocomputing, (2019)Triple-Granularity Contrastive Learning for Deep Multi-View Subspace Clustering., , , and . ACM Multimedia, page 2994-3002. ACM, (2023)Multi-view adaptive semi-supervised feature selection with the self-paced learning., , , and . Signal Process., (2020)NOODLE: Joint Cross-View Discrepancy Discovery and High-Order Correlation Detection for Multi-View Subspace Clustering., , , , and . ACM Trans. Knowl. Discov. Data, 18 (6): 151:1-151:23 (July 2024)ONION: Joint Unsupervised Feature Selection and Robust Subspace Extraction for Graph-based Multi-View Clustering., , , and . ACM Trans. Knowl. Discov. Data, 17 (5): 70:1-70:23 (June 2023)A Unified Framework for Graph-Based Multi-View Partial Multi-Label Learning., , , and . IEEE Access, (2023)One-step graph-based incomplete multi-view clustering., , , , , and . Multim. Syst., 30 (1): 32 (February 2024)Joint Original Space and Latent Space for Multi-view Spectral Clustering., , and . PAAP, page 1-6. IEEE, (2022)Diversity-induced consensus and structured graph learning for multi-view clustering., , and . Appl. Intell., 53 (10): 12237-12251 (May 2023)