Resource prediction can greatly assist resource selection and scheduling in a distributed resource sharing environment such as a computational grid. Existing resource prediction m...
We propose a solution to the problem of adaptive output regulation for nonlinear minimum-phase systems that does not rely upon conventional adaptation schemes to estimate the frequ...
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
This paper presents a human-aware software agent to support a human performing a task that demands substantial amounts of attention. The agent obtains human awareness in an adaptiv...
Tibor Bosse, Zulfiqar A. Memon, Jan Treur, Muhamma...
In this paper, adaptive noisy optimization on variants of the noisy sphere model is considered, i.e. optimization in which the same algorithm is able to adapt to several frameworks...