1. 2016
  2. Flexible State-Merging for learning (P)DFAs in Python

    Hammerschmidt, C., Loos, B., State, R., Engel, T. & Verwer, S., 2016, Proceedings of The 13th International Conference on Grammatical Inference: The JMLR Workshop and Conference, The Sequence PredictIction ChallengE (SPiCe). Verwer, S., van Zaanen, M. & Smetsers, R. (eds.). JMLR, Vol. 57. p. 154-159 6 p. (JMLR: Workshop and Conference Proceedings).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  3. Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: An Industrial Case

    Bueno, M. L. P., Hommersom, A., Lucas, P. J. F., Verwer, S. & Linard, A., 2016, Proceedings of the Eighth International Conference on Probabilistic Graphical Models : The JMLR Workshop and Conference PGM 2016. Antonucci, A., Corani, G. & de Campos, C. P. (eds.). JMLR, Vol. 52. p. 50-61 12 p. (JMLR: Workshop and Conference Proceedings).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  4. Learning Deterministic Finite Automata from Innite Alphabets

    Pellegrino, N., Hammerschmidt, C., Verwer, S. & Lin, Q., 2016, Proceedings of The 13th International Conference on Grammatical Inference: The JMLR Workshop and Conference, The Sequence PredictIction ChallengE (SPiCe). Verwer, S., van Zaanen, M. & Smetsers, R. (eds.). JMLR, Vol. 57. p. 69-72 5 p. (JMLR: Workshop and Conference Proceedings).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  5. Proceedings of the 13th International Conference on Grammatical Inference ICGI: JMLR Workshop and Conference Proceedings

    Verwer, S. (ed.), van Zaanen, M. (ed.) & Smetsers, R. (ed.), 2016, JMLR. 169 p. (JMLR: Workshop and Conference Proceedings)

    Research output: Book/ReportBook editingScientificpeer-review

  6. 2014
  7. Bigger is not always better: on the quality of hypotheses in active automata learning

    Smetsers, R., Volpato, M., Vaandrager, FW. & Verwer, SE., 2014, Proceedings of the 12th International Conference of Grammatical Inference. Clark, A., Kanazawa, M. & Yoshinaka, R. (eds.). p. 167-181 15 p. (JMLR Workshop and Conference Proceedings; vol. 34).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  8. Improving active Mealy machine learning for protocol conformance testing

    Aarts, F., Kuppens, H., Tretmans, J., Vaandrager, FW. & Verwer, SE., 2014, In : Machine Learning. 96, 1-2, p. 189-224 36 p.

    Research output: Contribution to journalArticleScientificpeer-review

  9. Merging partially labelled trees: hardness and a declarative programming solution

    Labarre, A. & Verwer, SE., 2014, In : IEEE - ACM Transactions on Computational Biology and Bioinformatics. 11, 2, p. 389-397 9 p.

    Research output: Contribution to journalArticleScientificpeer-review

  10. Regular inference as vertex coloring

    Florêncio, CC. & Verwer, SE., 2014, In : Theoretical Computer Science. 558, p. 18-34 17 p.

    Research output: Contribution to journalArticleScientificpeer-review

  11. 2011
  12. Learning Driving Behavior By Timed Syntactic Pattern Recognition

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2011, Proceedings of the International Joint Conference on Artificial Intelligence. Walsh, T. (ed.). American Association for Artificial Intelligence (AAAI), p. 1529-1534 6 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  13. The efficiency of identifying timed automata and the power of clocks

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2011, In : Information and Computation. 209, 3, p. 606-625 20 p.

    Research output: Contribution to journalArticleScientificpeer-review

  14. 2010
  15. A likelihood-ratio test for identifying probabilistic deterministic real-time automata from positive data

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2010, Grammatical Inference: Theoretical Results and Applications. Sempere, JM. & García, P. (eds.). Berlin: Springer, p. 203-216 14 p. (Lecture Notes in Computer Science; vol. 6339).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  16. Efficient Identification of Timed Automata: Theory and Practice

    Verwer, SE., 2010, Delft. 252 p.

    Research output: ThesisDissertation (TU Delft)

  17. Exact DFA Identification Using SAT Solvers

    Heule, MJH. & Verwer, SE., 2010, Grammatical Inference: Theoretical Results and Applications 10th International Colloquium, ICGI 2010. Sempere, JM. & García, P. (eds.). Berlin: Springer, p. 66-79 14 p. (Lecture Notes in Computer Science; vol. 6339).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  18. 2009
  19. One-Clock Deterministic Timed Automata Are Efficiently Identifiable in the Limit

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2009, Third International Conference, LATA 2009, Tarragona, Spain, April 2-8, 2009. Proceedings. Dediu, AH., Ionescu, AM. & Martin-Vide, C. (eds.). Berlin: Springer, p. 740-751 12 p. (Lecture Notes in Computer Science; vol. 5457).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  20. Using a satisfiability solver to identify deterministic finite state automata

    Heule, MJH. & Verwer, SE., 2009, BNAIC 2009 Benelux Conference on Artificial Intelligence. Calders, T., Tuyls, K. & Pechenizkiy, M. (eds.). Eindhoven: BNAIC, p. 91-98 8 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  21. 2008
  22. Efficiently learning simple timed automata

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2008, Induction of Process Models (IPM 2008). Bridewell, W., Calders, T., de Medeiros, A. K., Kramer, S., Pechenizkiy, M. & Todorovski, L. (eds.). Antwerp: University of Antwerp, p. 61-68 8 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  23. Efficiently learning timed models from observations

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2008, Benelearn 2008. Wehenkel, L., Geurts, P. & Maree, R. (eds.). Luik: University of Liege, p. 75-76 2 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  24. Polynomial distinguishability of timed automata

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2008, ICGI. Clark, A., Coste, F. & Miclet, L. (eds.). Springer, p. 238-251 14 p. (Lecture Notes in Artificial Intelligence; vol. 5278).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  25. 2006
  26. Identifying an automaton model for timed data

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2006, Proceedings of the Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn). Saeys, Y., Tsiporkova, E., Baets, B. D. & van de Peer, Y. (eds.). Benelearn, p. 57-64 8 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

  27. Identifying an automaton model for timed data (extended abstract)

    Verwer, SE., de Weerdt, MM. & Witteveen, C., 2006, Proceedings of the Belgium-Dutch Conference on Artificial Intelligence (BNAIC). Schobbens, P-Y., Vanhoof, W. & Schwanen, G. (eds.). BNVKI, p. 439-440 2 p.

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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