The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...
A technique for computing the switching activity of synchronous Finite State Machine (FSM) implementations including the influence of temporal correlation among the next state si...
Mikael Kerttu, Per Lindgren, Mitchell A. Thornton,...
We investigate the problem of learning optimal descriptors for a given classification task. Many hand-crafted descriptors have been proposed in the literature for measuring visua...
The problem of extracting continuous structures from noisy or cluttered images is a difficult one. Successful extraction depends critically on the ability to balance prior constra...
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...