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
Source: 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

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