Security at the physical layer (PHY) is a salient research topic in wireless systems, and
machine learning (ML) is emerging as a powerful tool for providing new data-driven security …

In this paper, we present a sparse correntropy framework for computing robust sparse
representations of face images for recognition. Compared with the state-of-the-art l 1 norm …

Robust sparse representation has shown significant potential in solving challenging
problems in computer vision such as biometrics and visual surveillance. Although several …

Principal component analysis (PCA) minimizes the mean square error (MSE) and is
sensitive to outliers. In this paper, we present a new rotational-invariant PCA based on …

Sparse adaptive channel estimation problem is one of the most important topics in
broadband wireless communications systems due to its simplicity and robustness. So far …

In this paper, we study the problem of robust feature extraction based on l 2, 1 regularized
correntropy in both theoretical and algorithmic manner. In theoretical part, we point out that …

The iterative closest point (ICP) algorithm has the advantage of high accuracy and fast
speed for point set registration, but it performs poorly when the point sets have a large …

Semisupervised learning (SSL) methods have been proved to be effective at solving the
labeled samples shortage problem by using a large number of unlabeled samples together …

The support vector machine (SVM) is a popular classifier in machine learning, but it is not
robust to outliers. In this paper, based on the Correntropy induced loss function, we propose …

Multi-view clustering has been a significant research problem in unsupervised clustering in
recent years and has important applications in computer vision, data mining and other fields …