Abstract. The generic (aka. black-box) group model is a valuable methodology for analyzing the computational hardness of number-theoretic problems used in cryptography. Since the p...
Andy Rupp, Gregor Leander, Endre Bangerter, Alexan...
This paper concerns the development of a new direction in machine learning, called natural induction, which requires from computergenerated knowledge not only to have high predicti...
Abstract—We present a new approach to event-driven simulation that does not use a centralized run-time event queue, yet is capable of handling arbitrary models, including those w...
Robert S. French, Monica S. Lam, Jeremy R. Levitt,...
In recent years, there have been some interesting studies on predictive modeling in data streams. However, most such studies assume relatively balanced and stable data streams but...
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...