Existing autocalibration techniques use numerical optimization algorithms that are prone to the problem of local minima. To address this problem, we have developed a method where ...
The problem of finding anomaly has received much attention recently. However, most of the anomaly detection algorithms depend on an explicit definition of anomaly, which may be i...
Ada Wai-Chee Fu, Oscar Tat-Wing Leung, Eamonn J. K...
We propose a novel variant of the (1 + 1)-CMA-ES that updates the distribution of mutation vectors based on both successful and unsuccessful trial steps. The computational costs o...
-- In previous work, Hu and Dill identified a common cause of BDD-size blowup in high-level design verification and proposed the method of implicitly conjoined invariants to addres...
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...