While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...
We introduce the problem of domain adaptation for content-based retrieval and propose a domain adaptation method based on relative aggregation points (RAPs). Content-based retriev...
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
— Mobile users are expected to be highly dynamic in next generation mobile networks. Additionally they will be served a wide variety of services with different transmission rates...
With our interest to improve our education in computer science, an understanding of how students learn about CS concepts, how different concepts are understood, as well as the con...
Mordechai Ben-Ari, Anders Berglund, Shirley Booth,...