Abstract
The present paper introduces a new model for teaching randomized learners. Our new model, though based on the classical teaching dimension model, allows to study the influence of various parameters such as the learner's memory size, its ability to provide or to not provide feedback, and the influence of the order in which examples are presented. Furthermore, within the new model it is possible to investigate new aspects of teaching like teaching from positive data only or teaching with inconsistent teachers. Furthermore, we provide characterization theorems for teachability from positive data for both ordinary teachers and inconsistent teachers with and without feedback. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Balbach, F. J., & Zeugmann, T. (2006). Teaching randomized learners. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4005 LNAI, pp. 229–243). Springer Verlag. https://doi.org/10.1007/11776420_19
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
