Supervised Non-negative Matrix Factorization Induced by Huber Loss
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-87358-5_17
Reference13 articles.
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3. Cai, D., He, X., Han, J., Huang, T.S.: Graph regularized nonnegative matrix factorization for data representation. IEEE Trans. Pattern Anal. Mach. Intell. 33(08), 1548–1560 (2011)
4. Guan, N., Tao, D., Luo, Z., Yuan, B.: Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent. IEEE Trans. Image Process. 20(7), 2030–2048 (2011)
5. He, M., Wei, F., Jia, X.: Globally maximizing, locally minimizing: regularized nonnegative matrix factorization for hyperspectral data feature extraction. In: 2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS), pp. 1–4 (2012)
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