Support vector machine (SVM) is a machine learning method based on statistical learning
theory. It has a lot of advantages, such as solid theoretical foundation, global optimization …

Due to its wide applicability, the problem of semi-supervised classification is attracting
increasing attention in machine learning. Semi-Supervised Support Vector Machines …

The least squares support vector machine (LS-SVM), like the SVM, is based on the margin-
maximization performing structural risk and has excellent power of generalization. In this …

Semi-supervised learning is one of the most promising learning paradigms in many practical
applications where few labeled samples are available. Among such learning models, semi …

Semi-supervised learning has attracted a great deal of attention in machine learning and
data mining. In this paper, we have proposed a novel Laplacian Twin Support Vector …

In this paper, we propose to reinforce the Self-Training strategy in semi-supervised mode by
using a generative classifier that may help to train the main discriminative classifier to label …

Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which
try to improve learning performance by exploiting unlabeled data. Though S3VMs have …

Semi-Supervised Support Vector Machines (S3VMs) are an appealing method for using
unlabeled data in classification: their objective function favors decision boundaries which do …

Support vector regression (SVR) and support vector classification (SVC) are popular
learning techniques, but their use with kernels is often time consuming. Recently, linear SVC …

The support vector machine is a new type of machine learning methods based on statistical
learning theory. Because of good promotion and a higher accuracy, support vector machine …