Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
This paper reports the application of evolutionary computation in the automatic generation of a neural network architecture.It is a usual practice to use trial and error to find a...
E. Vonk, Lakhmi C. Jain, L. P. J. Veelenturf, R. J...
The diversity of mobile devices and their limitations have raised many challenges for the actual deployment of mobile learning across institutions. The main objective of this work...
Abstract. In computer science methods to aid learning are very imporcause abstract models are used frequently. For this conventional teaching methods do not suffice. We have develo...
Beatrix Braune, Stephan Diehl, Andreas Kerren, Rei...