We propose regression modeling as an efficient approach for accurately predicting performance and power for various applications executing on any microprocessor configuration in a...
In the paper we present a new evolutionary algorithm for induction of regression trees. In contrast to the typical top-down approaches it globally searches for the best tree struct...
Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by...
Kernel logistic regression models, like their linear counterparts, can be trained using the efficient iteratively reweighted least-squares (IRWLS) algorithm. This approach suggest...
Model selection is an important ingredient of many machine learning algorithms, in particular when the sample size in small, in order to strike the right trade-off between overfitt...