In this study, we propose an improved semi-supervised support vector machine (SVM) based translation algorithm for brain-computer interface (BCI) systems, aiming at reducing the t...
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...
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
This paper deals with pattern rejection strategies for self-paced Brain-Computer Interfaces (BCI). First, it introduces two pattern rejection strategies not used yet for self-pace...