The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-...
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
We consider two new formulations for classification problems in the spirit of support vector machines based on robust optimization. Our formulations are designed to build in prote...
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...