In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly spa...
It is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (SVMs), to handle mismatches between the training and test da...
Highly available and resilient networks play a decisive role in today’s networked world. As network faults are inevitable and networks are becoming constantly intricate, finding...
Feng Liu, Antonis M. Hadjiantonis, Ha Manh Tran, M...
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...
In this paper an instructional framework is proposed for supporting personalised learning in the context of webbased adaptive educational hypermedia systems. A learning-focused ap...