Optimization algorithms for large margin multiclass recognizers are often too costly to handle ambitious problems with structured outputs and exponential numbers of classes. Optim...
— A heuristic is proposed to address free parameter selection for Support Vector Machines, with the goals of improving generalization performance and providing greater insensitiv...
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...