We consider the problem of binary classification where the classifier may abstain instead of classifying each observation. The Bayes decision rule for this setup, known as Chow...
Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshe...
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
We describe a fast Sequential Minimal Optimization (SMO) procedure for solving the dual optimization problem of the recently proposed Potential Support Vector Machine (P-SVM). The...
In the recent years support vector machines (SVMs) have been successfully applied to solve a large number of classification problems. Training an SVM, usually posed as a quadrati...
In this paper, we analyze the convergence of an iterative selftraining semi-supervised support vector machine (SVM) algorithm, which is designed for classi cation in small trainin...