The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
Abstract. This paper shows how a sparse hypermatrix Cholesky factorization can be improved. This is accomplished by means of efficient codes which operate on very small dense matri...
SIMD extension is one of the most common and effective technique to exploit data-level parallelism in today’s processor designs. However, the performance of SIMD architectures i...
Multilabel classification is a challenging research problem in which each instance is assigned to a subset of labels. Recently, a considerable amount of research has been concerned...
Muhammad Atif Tahir, Josef Kittler, Krystian Mikol...
— Directional antennas are a promising option for use in ad-hoc networks for a variety of reasons, such as increased spatial reuse, reduced interference and enabling more effici...