Reference : Learning Deterministic Finite Automata from Infinite Alphabets
Scientific congresses, symposiums and conference proceedings : Unpublished conference
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/28373
Learning Deterministic Finite Automata from Infinite Alphabets
English
Pellegrino, Gaetano mailto [Delft University of Technology > Faculty of Electrical Engineering, Mathematics and Computer Science]
Hammerschmidt, Christian mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Lin, Qin mailto [Delft University of Technology > Faculty of Electrical Engineering, Mathematics and Computer Science]
Verwer, Sicco mailto [Delft University of Technology > Faculty of Electrical Engineering, Mathematics and Computer Science]
Oct-2016
12
Yes
International
The 13th International Conference on Grammatical Inference
from 05-10-2016 to 07-10-2016
[en] passive learning ; deterministic finite automata ; regression
[en] We proposes an algorithm to learn automata infinite alphabets, or at least too large to enumerate. We apply it to define a generic model intended for regression, with transitions constrained by intervals over the alphabet. The algorithm is based on the Red \& Blue framework for learning from an input sample. We show two small case studies where the alphabets are respectively the natural and real numbers, and show how nice properties of automata models like interpretability and graphical representation transfer to regression where typical models are hard to interpret.
Interdisciplinary
Fonds National de la Recherche - FnR
R-AGR-0685-11-Z
Researchers
http://hdl.handle.net/10993/28373

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