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Robust Dimension Reduction for Clustering With Local Adaptive Learning.

, , , , and . IEEE Trans. Neural Networks Learn. Syst., 30 (3): 657-669 (2019)

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Fast Adaptive K-Means Subspace Clustering for High-Dimensional Data., , , , and . IEEE Access, (2019)Semi-supervised multi-label feature selection via label correlation analysis with l1-norm graph embedding., , , , and . Image Vis. Comput., (2017)Adaptive multi-view subspace clustering for high-dimensional data., , , and . Pattern Recognit. Lett., (2020)Robust Dimension Reduction for Clustering With Local Adaptive Learning., , , , and . IEEE Trans. Neural Networks Learn. Syst., 30 (3): 657-669 (2019)Improving SVM Classification with Imbalance Data Set., and . ICONIP (1), volume 5863 of Lecture Notes in Computer Science, page 389-398. Springer, (2009)Simplified Support Vector Machines Via Kernel-Based Clustering., , and . Australian Conference on Artificial Intelligence, volume 4304 of Lecture Notes in Computer Science, page 1189-1195. Springer, (2006)A Hybrid Method for Speeding SVM Training., , and . NGITS, volume 4032 of Lecture Notes in Computer Science, page 312-320. Springer, (2006)Unsupervised feature analysis with sparse adaptive learning., , , and . Pattern Recognit. Lett., (2018)Semi-supervised adaptive feature analysis and its application for multimedia understanding., , , , and . Multimedia Tools Appl., 77 (3): 3083-3104 (2018)Fast training Support Vector Machines using parallel sequential minimal optimization., , , , and . ISKE, page 997-1001. IEEE, (2008)