We extend multiclass SVM to multiple prototypes per class. For this framework, we give a compact constrained quadratic problem and we suggest an efficient algorithm for its optimi...
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
This paper develops algorithms to train support vector machines when training data are distributed across different nodes, and their communication to a centralized processing unit...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...