In this study, a support vector machine (SVM) classifies real world data of cytogenetic signals measured from fluorescence in-situ hybridization (FISH) images in order to diagnose...
Support vector machines (SVMs), though accurate, are not preferred in applications requiring great classification speed, due to the number of support vectors being large. To overc...
S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCos...
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
Marcelo Espinoza, Johan A. K. Suykens, Bart De Moo...