To handle this problem, in this paper, we propose a novel Robust Capped L1-norm Twin Support Vector Machine with Privileged Information (R-CTSVM+). The proposed pair of regularization functions (up- and down-bound) can definitely help to increase the learning model's tolerance to disturbance,...
To handle this problem, in this paper, we propose a novel Robust Capped L1-norm Twin Support Vector Machine with Privileged Information (R-CTSVM+). The proposed pair of regularization functions (up- and down-bound) can definitely help to increase the learning model’s tolerance to disturbance...
The capped L1-norm with upper bound value is used to construct the optimization problem instead of L2-norm, which weakens the influence of outliers and noise points on the construction of two hyperplanes to a certain extent and enhances the robustness of the model. In addition, a simple and ...
The used norm can inherit the advantage of the 1 norm, which is robust to label noise to some extent. Moreover, the capped 1 norm can adaptively find extremely mislabeled instances and eliminate the corresponding negative influence. Additionally, the proposed algorithm makes full use of the ...
Recently, L1-norm distance measure based Linear Discriminant Analysis (LDA) techniques have been shown to be robust against outliers. However, these method... Q Ye,L Fu,Z Zhao,... - 《Neural Networks》 被引量: 0发表: 2018年 L2,1 Norm and its Applications This formulation induce sparsity...
Capped L1-normVGGnetCIFARConvolutional neural networkFLOPsThe blistering progress of convolutional neural networks (CNNs) in numerous applications of the real-world usually obstruct by a surge in network volume and computational cost. Recently, researchers concentrate on eliminating these issues by ...
Capped L1-normVGGnetCIFARConvolutional neural networkFLOPsThe blistering progress of convolutional neural networks (CNNs) in numerous applications of the real-world usually obstruct by a surge in network volume and computational cost. Recently, researchers concentrate on eliminating these issues by ...
Huang, "Robust dictionary learning with capped l1-norm," in Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015, pp. 3590-3596.Jiang, W.; Nie, F.; and Huang, H. 2015. Robust dictio- nary learning with capped l1 norm. Twenty-Fourth Inter- ...
For the last problem, many L1-norm based methods, such as PCA-L1 [9] and TPCA-L1 [10], were proposed. These kinds of methods replace the L2-norm with the L1-norm as basic measurements, so that their robustness can be improved. Although L1-norm based methods are more robust, they ...
FRTELM first replaced the inequality constraints in TELM with equality constraints, and then introduced the cappedL1-norm distance metric to replace theL2-norm distance metric in TELM. FRTELM not only retains the advantages of TELM, but also overcomes the shortcomings of TELM exaggeration of ...