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MvMENSVM : A multi-view support vector machine with manifold elastic net regularization
DOI:10.1016/j.eswa.2026.131666.png)
Abstract
En 中文
• A novel multi-view SVM (MvMENSVM) unifying manifold learning with elastic net regularization. • Robust Huberized hinge loss for enhanced tolerance to label noise and outliers. • Joint elastic net regularization enables sparse feature selection across all views. • Adaptive manifold term preserves data geometry using learnable graph coefficients. • Efficient proximal gradient algorithm with proven convergence guarantees.
Keywords:
Multi-view learning
Support vector machine
Manifold regularization
Elastic net
Proximal gradient method
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W

