This paper describes how meta-level theories are used for analytic learning in M U L T I - T A C . M U L T I - T A C operationalizes generic heuristics for constraint-satisfaction...
Pervasive games have been proposed as a suitable way to support learning, especially in places rich in information, as for example museums and cultural heritage sites. This paper r...
Carmelo Ardito, Rosa Lanzilotti, Dimitris Raptis, ...
RNA genes lack most of the signals used for protein gene identification. A major shortcoming of previous discriminative methods to distinguish functional RNA (fRNA) genes from oth...
Richard F. Meraz, Xiaofeng He, Chris H. Q. Ding, S...
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...