: This paper presents a feature selection technique based on distributional differences for efficient machine learning. Initial training data consists of data including many featur...
We investigate the connections between the process algebra for hybrid systems of Bergstra and Middelburg and the formalism of hybrid automata of Henzinger et al. We give interpreta...
While methods for comparing two learning algorithms on a single data set have been scrutinized for quite some time already, the issue of statistical tests for comparisons of more ...
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
We determine the asymptotic behaviour of the function computed by support vector machines (SVM) and related algorithms that minimize a regularized empirical convex loss function i...