Please use this identifier to cite or link to this item:
https://doi.org/10.1007/978-3-642-00982-2_4
| Title: | Hypothesis spaces for learning | Authors: | Jain, S. | Issue Date: | 2009 | Citation: | Jain, S. (2009). Hypothesis spaces for learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5457 : 43-58. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-00982-2_4 | Abstract: | In this paper we survey some results in inductive inference showing how learnability of a class of languages may depend on hypothesis space chosen. We also discuss results which consider how learnability is effected if one requires learning with respect to every suitable hypothesis space. Additionally, optimal hypothesis spaces, using which every learnable class is learnable, is considered. © Springer-Verlag Berlin Heidelberg 2009. | Source Title: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | URI: | http://scholarbank.nus.edu.sg/handle/10635/41059 | ISBN: | 9783642009815 | ISSN: | 03029743 | DOI: | 10.1007/978-3-642-00982-2_4 |
| Appears in Collections: | Staff Publications |
Show full item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.