An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the KuhnTucker conditions on all previously se...
— We present here a hardware–friendly version of the Support Vector Machine (SVM), which is useful to implement its feed–forward phase on limited–resources devices such as ...
Although version space support vector machines (VSSVMs) are a successful approach to reliable classification [6], they are restricted to separable data. This paper proposes gener...
Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, Ni...
This paper presents a summary of the issues discussed during the one day workshop on "Support Vector Machines (SVM) Theory and Applications" organized as part of the Adv...
Abstract. We report about some experiments on the fingerprint database NIST-4 using different combinations of Support Vector Machine (SVM) classifiers. Images have been preprocesse...