We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
Motivation: Remote homology detection between protein sequences is a central problem in computational biology. Supervised learning algorithms based on support vector machines are ...
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...