Abstract. In this paper, we investigate the application of adaptive ensemble models of Extreme Learning Machines (ELMs) to the problem of one-step ahead prediction in (non)stationa...
Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutil...
Computational grid provides a platform for exploiting various computational resources over wide area networks. One of the concerns in implementing computational grid environment is...
We consider the application of machine learning techniques for sequence modeling to Information Retrieval (IR) and surface Information Extraction (IE) tasks. We introduce a generi...
Massih-Reza Amini, Hugo Zaragoza, Patrick Gallinar...
Robot motion planning in a dynamic cluttered workspace requires the capability of dealing with obstacles and deadlock situations. The paper analyzes situations where the robot is ...
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...