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Type of addressPostal address
Postal codeYO10 5GH
CountryUnited Kingdom
Address lines
  • Computer Science
    University of York
    Deramore Lane
    York
    YO10 5GH

Phone: (01904) 325676

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Dr. Dimitar Lubomirov Kazakov

Senior Lecturer

  1. 2020
  2. CONNER: A Concurrent ILP Learner in Description Logic

    Algahtani, E. & Kazakov, D. L., 5 Jun 2020, Inductive Logic Programming: 29th International Conference, ILP 2019. Springer, p. 1-15 15 p. (LNAI; no. 11770).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  3. 2019
  4. Unsupervised Learning of Functional Groups for Computational Chemistry

    Erten, C., Algahtani, E., Fairlamb, I. J. S., Garcia-Padilla, E., Lynam, J. M., Manandhar, S., Slattery, J. M. & Kazakov, D. L., 5 Sep 2019, p. 1-4.

    Research output: Contribution to conferenceAbstract

  5. Deep Reinforcement Learning Based Parameter Control in Differential Evolution

    Sharma, M., Komninos, A., López-Ibáñez, M. & Kazakov, D. L., 13 Jul 2019, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference. ACM, p. 709-717 (ACM Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  6. Detecting Causal Links between Financial News and Stocks

    Qu, H. & Kazakov, D. L., 11 Jul 2019, Proceedings of IEEE Conference on Computational Intelligence for Financial Engineering and Economics: (CIFEr 2019). Shenzhen, China: IEEE, p. 156-163 9 p. (IEEE Symposium on Computational Intelligence for Financial Engineering and Economics).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  7. 2018
  8. Performance Assessment of Recursive Probability Matching for Adaptive Operator Selection in Differential Evolution

    Sharma, M., López-Ibáñez, M. & Kazakov, D. L., Sep 2018, 15th Intl Conf. on Parallel Problem Solving from Nature: (PPSN 2018). SPRINGER-VERLAG BERLIN, p. 321-333 13 p. (LNCS).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  9. Learning from Ordinal Data with Inductive Logic Programming in Description Logic

    Qomariyah, N. N. & Kazakov, D. L., 29 Mar 2018, Late Breaking Papers of the 27th International Conference on Inductive Logic Programming. Lachiche, N. & Vrain, C. (eds.). http://ceur-ws.org/Vol-2085/: CEUR Workshop Proceedings, Vol. 2085. p. 38-50 13 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  10. Learning implicational models of universal grammar parameters

    Kazakov, D. L., Cordoni, G., Algahtani, E., Ceolin, A., Irimia, M-A., Kim, S-S., Michelioudakis, D., Radkevich, N., Guardiano, C. & Longobardi, G., 29 Jan 2018, The Evolution of Language: Proceedings of the 12th International Conference (EVOLANGXII). Cuskley, C., Flaherty, M., Little, H., McCrohon, L., Ravignani, A. & Verhoef, T. (eds.). Torun, Poland: Online at http://evolang.org/torun/proceedings/papertemplate.html?p=176, 10 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  11. GPU-Accelerated Hypothesis Cover Set Testing for Learning in Logic

    Algahtani, E. & Kazakov, D. L., 2018, CEUR Proceedings of the 28th International Conference on Inductive Logic Programming. CEUR Workshop Proceedings

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  12. 2017
  13. Building Dialectal Arabic Corpora

    Elgabou, H. A. M. & Kazakov, D. L., 7 Sep 2017, The First Workshop on Human-Informed Translation and Interpreting Technology (HiT-IT). p. 52-57 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  14. Learning from Ordinal Data with Inductive Logic Programming in Description Logic

    Qomariyah, N. N. & Kazakov, D. L., Sep 2017, Online proceedings of the 27th conference on Inductive Logic Programming.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  15. Learning Binary Preference Relations: Analysis of Logic-based versus Statistical Approaches

    Qomariyah, N. N. & Kazakov, D. L., 27 Aug 2017, p. 30-34. 5 p.

    Research output: Contribution to conferencePaper

  16. 2016
  17. Syntactic theory and the science of (language) history

    Longobardi, G., Michelioudakis, D., Guardiano, C., Irimia, M-A., Radkevich, N., Kim, S-S., Cordoni, G., Ceolin, A. & Kazakov, D. L., Sep 2016.

    Research output: Contribution to conferenceAbstract

  18. Integrating Time Series with Social Media Data in an Ontology for the Modelling of Extreme Financial Events

    Qu, H., Sardelich Nascimento, M., Qomariyah, N. N. & Kazakov, D. L., 23 May 2016, LREC 2016 Proceedings. Khan, F., Vintar, Š., Araúz, P. L., Faber, P., Frontini, F., Parvizi, A., Simeunović, L. G. & Unger, C. (eds.). European Language Resources Association (ELRA), Vol. Joint Second Workshop on Language and Ontology & Terminology and Knowledge Structures. p. 57-63

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  19. 2015
  20. Learning Ordinary Differential Equations for Macroeconomic Modelling

    Georgiev, Z. & Kazakov, D. L., Dec 2015, IEEE SSCI 2015: 2015 IEEE Symposium Series on Computational Intelligence. IEEE, p. 905-909 5 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  21. 2014
  22. 2013
  23. Using parallel corpora for word sense disambiguation

    Shahid, A. R. & Kazakov, D. L., 2013, RANLP-13. Hissar, Bulgaria

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  24. 2012
  25. A learning adaptive Bollinger band system

    Butler, M. R. & Kazakov, D. L., 2012, 2012 IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr 2012): New York City, New York, USA, 29-30 March 2012. New York: IEEE, p. 40-47 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  26. Testing Implications of the Adaptive Market Hypothesis via Computational Intelligence

    Kazakov, D. L. & Butler, M. R., 2012, Computational Intelligence for Financial Engineering & Economics (CIFEr), 2012 IEEE Conference on . IEEE, p. 1-8

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  27. 2011
  28. The effects of variable stationarity in a financial time-series on Artificial Neural Networks

    Butler, M. & Kazakov, D., 1 Apr 2011, 2011 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr). Paris: IEEE, p. 1 -8 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  29. Probabilistic Instruction Cache Analysis using Bayesian Networks

    Bartlett, M., Bate, I., Cussens, J. & Kazakov, D., 2011, Proceedings of the 17th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2011). Vol. 1. p. 233 - 242

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  30. 2010
  31. Modeling the behavior of the stock market with an Artificial Immune System

    Butler, M. & Kazakov, D., 1 Jul 2010, p. 1 -8.

    Research output: Contribution to conferencePaper

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