Abstract
In the recent development of various models of learning inspired by the PAC learning model (introduced by Valiant) there has been a trend towards models which are as representation independent as possible. We review this development and discuss the advantages of representation independence. Motivated by the research in learning, we propose a framework for studying the combinatorial properties of representations.
Cite
CITATION STYLE
Warmuth, M. K. (1989). Towards representation independence in PAC learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 397 LNAI, pp. 78–103). Springer Verlag. https://doi.org/10.1007/3-540-51734-0_53
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
