Learnability of probabilistic automata via oracles
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Guttman, Omri; Vishwanathan, S; Williamson, Robert
Description
Efficient learnability using the state merging algorithm is known for a subclass of probabilistic automata termed μ-distinguishable. In this paper, we prove that state merging algorithms can be extended to efficiently learn a larger class of automata. In
Collections | ANU Research Publications |
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Date published: | 2005 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/82367 |
Source: | Algorithmic Learning Theory: Proceedings of the 16th International Conference on Algorithmic Learning Theory (ALT-05) - LNAI 3734 |
DOI: | 10.1007/11564089_15 |
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01_Guttman_Learnability_of_probabilistic_2005.pdf | 194.4 kB | Adobe PDF | Request a copy |
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