Abstract
In this paper we extend the PAC learning algorithm due to Clark and Thollard for learning distributions generated by PDFA to automata whose transitions may take varying time lengths, governed by exponential distributions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Carrasco, R.C.: Accurate computation of the relative entropy between stochastic regular grammars. RAIRO (Theoretical Informatics and Applications) 31(5), 437–444 (1997)
Castro, J., Gavaldà, R.: Towards feasible PAC-learning of probabilistic deterministic finite automata. In: Clark, A., Coste, F., Miclet, L. (eds.) ICGI 2008. LNCS (LNAI), vol. 5278, pp. 163–174. Springer, Heidelberg (2008)
Clark, A., Thollard, F.: PAC-learnability of probabilistic deterministic finite state automata. Journal of Machine Learning Research (2004)
Dupont, P., Denis, F., Esposito, Y.: Links between probabilistic automata and hidden markov models: probability distributions, learning models and induction algorithms. Pattern Recognition 38(9), 1349–1371 (2005)
Gavaldà, R., Keller, P.W., Pineau, J., Precup, D.: PAC-learning of markov models with hidden state. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 150–161. Springer, Heidelberg (2006)
Guttman, O., Vishwanathan, S.V.N., Williamson, R.C.: Learnability of probabilistic automata via oracles. In: Jain, S., Simon, H.U., Tomita, E. (eds.) ALT 2005. LNCS (LNAI), vol. 3734, pp. 171–182. Springer, Heidelberg (2005)
Palmer, N., Goldberg, P.W.: PAC-learnability of probabilistic deterministic finite state automata in terms of variation distance. Theor. Comput. Sci. 387(1), 18–31 (2007)
Poggi, N., Berral, J.L., Moreno, T., Gavaldà, R., Torres, J.: Automatic detection and banning of content stealing bots for e-commerce. In: NIPS 2007 Workshop on Machine Learning in Adversarial Environments for Computer Security (2007), http://mls-nips07.first.fraunhofer.de/
Poggi, N., Moreno, T., Berral, J.L., Gavaldà, R., Torres, J.: Web customer modeling for automated session prioritization on high traffic sites. In: Conati, C., McCoy, K., Paliouras, G. (eds.) UM 2007. LNCS (LNAI), vol. 4511, pp. 450–454. Springer, Heidelberg (2007)
Poggi, N., Moreno, T., Berral, J.L., Gavaldà, R., Torres, J.: Self-adaptive utility-based web session management. Computer Networks 53(10), 1712–1721 (2009)
Ron, D., Singer, Y., Tishby, N.: On the learnability and usage of acyclic probabilistic finite automata. J. Comput. Syst. Sci. 56(2), 133–152 (1998)
Vidal, E., Thollard, F., de la Higuera, C., Casacuberta, F., Carrasco, R.C.: Probabilistic finite-state machines - part I. IEEE Trans. Pattern Anal. Mach. Intell. 27(7), 1013–1025 (2005)
Vidal, E., Thollard, F., de la Higuera, C., Casacuberta, F., Carrasco, R.C.: Probabilistic finite-state machines - part II. IEEE Trans. Pattern Anal. Mach. Intell. 27(7), 1026–1039 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Balle, B., Castro, J., Gavaldà, R. (2010). Learning PDFA with Asynchronous Transitions. In: Sempere, J.M., García, P. (eds) Grammatical Inference: Theoretical Results and Applications. ICGI 2010. Lecture Notes in Computer Science(), vol 6339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15488-1_24
Download citation
DOI: https://doi.org/10.1007/978-3-642-15488-1_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15487-4
Online ISBN: 978-3-642-15488-1
eBook Packages: Computer ScienceComputer Science (R0)