Support vector machines have gotten wide acceptance for their high generalization ability for real world applications. But the major drawback is slow training for classification p...
In this paper, we analyze the convergence of an iterative selftraining semi-supervised support vector machine (SVM) algorithm, which is designed for classi cation in small trainin...
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...
The human neural responses associated with cognitive events, referred as event related potentials (ERPs), can provide reliable inference for target image detection. Incremental le...
Yonghong Huang, Deniz Erdogmus, Misha Pavel, Kenne...