SAMN: A Sample Attention Memory Network Combining SVM and NN in One Architecture

no code implementations • 25 Sep 2023 • Qiaoling Yang, Linkai Luo, Haoyu Zhang, Hong Peng, Ziyang Chen

To address this, we propose a sample attention memory network (SAMN) that effectively combines SVM and NN by incorporating sample attention module, class prototypes, and memory block to NN.

MaxMin-L2-SVC-NCH: A Novel Approach for Support Vector Classifier Training and Parameter Selection

no code implementations • 14 Jul 2023 • Linkai Luo, Qiaoling Yang, Hong Peng, Yiding Wang, Ziyang Chen

We first formulate the training and parameter selection of SVC as a minimax optimization problem named as MaxMin-L2-SVC-NCH, in which the minimization problem is an optimization problem of finding the closest points between two normal convex hulls (L2-SVC-NCH) while the maximization problem is an optimization problem of finding the optimal Gaussian kernel parameters.