Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...
Abstract. We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-...
Abstract. We compared a support vector machine (SVM) with a back propagation neural network (BPNN) for the task of text classification of XiangShan science conference (XSSC) web do...
Abstract. We present a hybrid machine learning approach for information extraction from unstructured documents by integrating a learned classifier based on the Maximum Entropy Mod...
Abstract. This paper describes a novel fuzzy rule-based modeling approach for some slow industrial processses. Structure identification is realized by clustering and support vecto...