Krzysztof Gr¹bczewski
Department of Informatics
Nicolaus Copernicus University
Torun, Poland 		Toruñ, February 3, 2012

List of publications

Theses:

  1. Gr¹bczewski K (1994) Systemy dowodzenia twierdzeñ i ich implementacje w pakiecie ,,Isabelle''. Master's thesis, Nicolaus Copernicus University, Toruñ, Poland.
  2. Gr¹bczewski K (2003) Zastosowanie kryterium separowalnoœci do generowania regu³ klasyfikacji na podstawie baz danych. PhD thesis, Systems Research Institute, Polish Academy of Sciences, Warszawa, Poland.

Book chapters:

  1. Duch W, Adamczak R, Gr¹bczewski K, ¯al G, Hayashi Y (1999) Fuzzy and crisp logical rule extraction methods in application to medical data. Fuzzy Systems in Medicine, Springer 1999.
  2. Duch W, Jankowski N, Gr¹bczewski K, Adamczak R, Optimization and interpretation of rule-based classifiers, Advances in Soft Computing, Physica-Verlag (Springer) 2000, pages 1-13.
  3. Gr¹bczewski K, Duch W, Adamczak R, Neuronowe metody odkrywania wiedzy w danych. Biocybernetyka 2000, Tom 6: Sieci neuronowe (red. W. Duch, J. Korbicz, L. Rutkowski i R. Tadeusiewicz), III.20, pages 637-662.
  4. Duch W, Biesiada J, Winiarski T, Grudziñski K, Gr¹bczewski K, Feature selection based on information theory filters and feature elimination wrapper methods. Neural Networks and Soft Computing, Springer 2002.
  5. Gr¹bczewski K, Duch W, Forests of decision trees. Neural Networks and Soft Computing, Springer 2002.
  6. Gr¹bczewski K, Jankowski N, Mining for complex models comprising feature selection and classification, In: Feature extraction, foundations and applications, Editors: Guyon I, Gunn S, Nikravesh M, Zadeh L, Studies in Fuzziness and Soft Computing. Physica-Verlag, Springer 2006, pages 473-489.
  7. Jankowski N, Gr¹bczewski K, Learning Machines, In: Feature extraction, foundations and applications, Editors: Guyon I, Gunn S, Nikravesh M, Zadeh L, Studies in Fuzziness and Soft Computing. Physica-Verlag, Springer 2006, pages 29-64.
  8. Jankowski N, Gr¹bczewski K, Learning machines information distribution system with example applications, In: Computer Recognition Systems 2, Editors: Kurzyñski M, Pucha³a E, WoŸniak M, ¯o³nierek A, Advances in Soft Computing, Springer, 2007, pages 205-215.
  9. Jankowski N, Gr¹bczewski K, Universal Meta-Learning Architecture and Algorithms, In: Meta-Learning in Computational Intelligence, Editors: Jankowski N, Duch W, Gr¹bczewski K, Studies in Computational Intelligence, Springer Berlin / Heidelberg, 2011, Vol. 358, pages 1-76.
  10. Gr¹bczewski K, Unified View of Decision Tree Learning Machines for the Purpose of Meta-learning, In: Computer Recognition Systems 4, Editors: Burduk R, Kurzyñski M, WoŸniak M, ¯o³nierek A, Advances in Intelligent and Soft Computing, Springer Berlin / Heidelberg, 2011, Vol. 95, pages 147-155.

Reviewed articles:

  1. Paulson L, Gr¹bczewski K (1996) Mechanizing Set Theory - Cardinal Arithmetic and the Axiom of Choice. Journal of Automated Reasoning 17, pages 291-323.
  2. Duch W, Adamczak R, Gr¹bczewski K (1998) Extraction of logical rules from backpropagation networks, Neural Processing Letters 7, pages 1-9.
  3. Duch W, Adamczak R, Gr¹bczewski K, ¯al G (1999) Hybrid neural-global minimization method of logical rule extraction, Int. Journal of Advanced Computational Intelligence.
  4. Duch W, Adamczak R, Gr¹bczewski K, Jankowski N, Neural methods of knowledge extraction, Control and Cybernetics 29 (4) (2000), pages 997-1018.
  5. Duch W, Adamczak R, Gr¹bczewski K, A new methodology of extraction, optimization and application of crisp and fuzzy logical rules. IEEE Transactions on Neural Networks 12 (2001), pages 277-306.
  6. Duch W, Adamczak R, Gr¹bczewski K (1996) Extraction of logical rules from training data using backpropagation networks, The 1st Online Workshop on Soft Computing, 19-30.Aug.1996, pages 25-30.
  7. Duch W, Adamczak R, Gr¹bczewski K (1996) Extraction of logical rules from training data using backpropagation networks CAI'96, First Polish Conference on Theory and Applications of Artificial Intelligence, £ódŸ, 19-21.12.1996, pages 171-178
  8. Duch W, Adamczak R, Gr¹bczewski K (1996). Constrained backpropagation for feature selection and extraction of logical rules, CAI'96, First Polish Conference on Theory and Applications of Artificial Intelligence, £ódŸ, 19-21.12.1996, pages 163-170.
  9. Duch W, Adamczak R, Gr¹bczewski K, Constrained MLP and density estimation for extraction of crisp logical rules from data. ICONIP'97, New Zealand, Nov.1997, pages 831-834.
  10. Duch W, Adamczak R, Gr¹bczewski K (1997) Extraction of crisp logical rules using constrained backpropagation networks, International Conference on Artificial Neural Networks (ICNN'97), Houston, 9-12.6.1997, pages 2384-2389.
  11. Duch W, Adamczak R, Gr¹bczewski K, Ishikawa M, Ueda H (1997). Extraction of crisp logical rules using constrained backpropagation networks - comparison of two new approaches, European Symposium on Artificial Neural Networks (ESANN'97), Bruge 16-18.4.1997, pages 109-114.
  12. Duch W, Adamczak R, Gr¹bczewski (1997) Logical rules for classification of medical data using ontogenic neural algorithm. Solving Engineering Problems with Neural Networks, International Conference EANN'97, Stockholm, 16-18.06.1997, pages 199-202.
  13. Duch W, Adamczak R, Gr¹bczewski K, Extraction of logical rules from medical datasets, Third Conference on Neural Networks and Their Applications, Kule, October 1997, pages 707-712.
  14. Duch W, Adamczak R, Gr¹bczewski K, Jankowski N, ¯al G, Medical diagnosis support using neural and machine learning methods, International Conference EANN'98, Gibraltar, 10-12.06.1998, pages 292-295.
  15. Duch W, Adamczak R, Gr¹bczewski K, ¯al G, Hybrid neural-global minimization logical rule extraction method for medical diagnosis support, Intelligent Information Systems VII, Malbork, Poland, 15-19.06.1998, pages 85-94.
  16. Duch W, Adamczak R, Gr¹bczewski K, ¯al G, A hybrid method for extraction of logical rules from data. Second Polish Conference on Theory and Applications of Artificial Intelligence, £ódŸ, 28-30 Sept. 1998, pages 61-82.
  17. Duch W, Adamczak R, Gr¹bczewski K (1999) Neural optimization of linguistic variables and membership functions. International Conference on Neural Information Processing (ICONIP'99), Perth, Australia, Nov. 1999, Vol. II, pages 616-621.
  18. Duch W, Adamczak R, Gr¹bczewski K (1999) Neural methods for analysis of psychometric data., International Conference EANN'99, Warsaw, 13-15.09.1999, pages 45-50.
  19. Duch W, Adamczak R, Gr¹bczewski K (1999) Optimization of logical rules derived by neural procedures, 1999 International Joint Conference on Neural Networks, Washington, July 1999, paper no. 741.
  20. Duch W, Gr¹bczewski K (1999) Searching for optimal MLP, 4th Conference on Neural Networks and Their Applications, Zakopane, May 1999, pages 65-70.
  21. Gr¹bczewski K, Duch W (1999) A general purpose separability criterion for classification systems, 4th Conference on Neural Networks and Their Applications, Zakopane, May 1999, pages 203-208.
  22. Duch W, Adamczak R, Gr¹bczewski K (1999) Methodology of extraction, optimization and application of logical rules, Intelligent Information Systems VIII, Ustroñ, Poland, 14-18.06.1999, pages 22-31.
  23. Gr¹bczewski K, Duch W, The separability of split value criterion. 5th Conference on Neural Networks and Soft Computing, Zakopane, June 2000, pages 201-208.
  24. Duch W, Gr¹bczewski K, Adamczak R, Grudziñski K, Hippe Z.S. (2001) Rules for melanoma skin cancer diagnosis. KOSYR, Wroc³aw 2001, pages 59-68.
  25. Duch W, Gr¹bczewski K, Heterogeneous adaptive systems. World Congress of Computational Intelligence, 2002.
  26. Gr¹bczewski K, Duch W, Heterogeneous forests of decision trees. International Conference on Artificial Neural Networks (ICANN) 2002.
  27. Duch W, Winiarski T, Gr¹bczewski K, Biesiada J, Kachel A, Feature selection based on information theory, consistency and separability indices. International Conference on Neural Information Processing (ICONIP), Vol. IV, pages 1951-1955, Singapore 2002.
  28. Gr¹bczewski K, Jankowski N, Transformations of symbolic data for continuous data oriented models. International Conference on Artificial Neural Networks/International Conference on Neural Information Processing (ICANN/ICONIP) 2003.
  29. Jankowski N, Gr¹bczewski K, Toward optimal SVM. Artificial Intelligence and Applications (AIA) 2003.
  30. Gr¹bczewski K, SSV Criterion based discretization for Naive Bayes Classifiers. Artificial Intelligence and Soft Computing - ICAISC 2004, Lecture Notes in Artificial Intelligence, pages 574-579.
  31. Gr¹bczewski K, Jankowski N, Feature Selection with Decision Tree Criterion, Fifth International conference on Hybrid Intelligent Systems, Rio de Janeiro, Brasil, 2005, pages 212-217.
  32. Jankowski N, Gr¹bczewski K, Heterogenous Committees with Competence Analysis, Fifth International conference on Hybrid Intelligent Systems, Rio de Janeiro, Brasil, 2005, pages 417-422.
  33. Duch W, Jankowski N, Gr¹bczewski K, Computational intelligence methods for information understanding and information management, The 4th International Conference on Information and Management Sciences (IMS2005), Kunming, China, 2005, pages 281-287.
  34. Gr¹bczewski K, Jankowski N, Meta-learning architecture for knowledge representation and management in computational intelligence, International Journal of Information Technology and Intelligent Computing, vol.2 no.2, 2007.
  35. Gr¹bczewski K, Jankowski N, Versatile and Efficient Meta-Learning Architecture: Knowledge Representation and Management in Computational Intelligence, IEEE Symposium Series on Computational Intelligence (SSCI 2007), Honolulu, pages 51-58.
  36. Jankowski N, Gr¹bczewski K, Handwritten Digit Recognition - Road to Contest Victory, IEEE Symposium Series on Computational Intelligence (SSCI 2007), Honolulu, pages 491-498.
  37. Jankowski N, Gr¹bczewski K, Gained knowledge exchange and analysis for meta-learning, Proceedings of International Conference on Machine Learning and Cybernetics, IEEE Press, 2007, pages 795-802.
  38. Gr¹bczewski K, Jankowski N, Control of complex machines for meta-learning in computational intelligence. Computational Intelligence, Man-Machine Systems and Cybernetics, 2007, pages 287-293.
  39. Gr¹bczewski K, Jankowski N, Meta-learning with machine generators and complexity controlled exploration. Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, Springer, Vol. 5097, 2008, pages 545-555.
  40. Jankowski N, Gr¹bczewski K, Building meta-learning algorithms basing on search controlled by machine complexity. IEEE World Congress on Computational Intelligence, Hong Kong, 1-6 June 2008, pages 3600-3607.
  41. Jankowski N, Gr¹bczewski K, Increasing efficiency of data mining systems by machine unification and double machine cache, Artificial Intelligence and Soft Computing, Lecture notes in computer science, Springer, 2010, pages 380-387.
  42. Gr¹bczewski K, Jankowski K, Task Management in Advanced Computational Intelligence System, Artificial Intelligence and Soft Computing, Lecture notes in computer science, Springer, 2010, pages 331-338.
  43. Gr¹bczewski K, Jankowski N, Saving time and memory in computational intelligence system with machine unification and task spooling, Knowledge-Based Systems, Elsevier Science Publishers, Amsterdam, 2011, Vol. 24, Issue 5, pages 570-588.
  44. Gr¹bczewski K, Separability of Split Value Criterion with Weighted Separation Gains, Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2011, Vol. 6871, pages 88-98.
  45. Gr¹bczewski K, Validated Decision Trees versus Collective Decisions, Computational Collective Intelligence. Technologies and Applications, Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2011, Vol. 6923, pages 342-351.

Non-reviewed publications:

  1. Duch W, Adamczak R, Gr¹bczewski K, Grudziñski K, Jankowski N, Naud N, Extraction of knowledge from data using Computational Intelligence methods. In: ICONIP-2000, 7th International Conference on Neural Information Processing, Nov. 2000, Dae-jong, Korea (tutorial, separate brochure, 54 pages).
  2. Duch W, Adamczak R, Gr¹bczewski K, Grudziñski K, Jankowski N, Naud N, Understanding the data: extraction, optimization and interpretation of logical rules. In: International Joint Conference on Neural Networks 2000 (IJCNN) (tutorial, separate brochure, 70 pages).
  3. Duch W, Adamczak R, Gr¹bczewski K, Grudziñski K, Jankowski N, Naud N, Extraction of Knowledge from Data using Computational Intelligence Methods. In: International Conference on Artificial Neural Networks (ICANN), Vienna, 21-25.08.2001 (tutorial, separate brochure, 63 pages).
  4. Gr¹bczewski K, and Jankowski N, Meta-learning as scheme-based search with complexity control. International Joint Conference on Neural Network. Workshop on Meta-Learning. 2007, pages 3-8.
  5. Duch W, Gr¹bczewski K, and Jankowski N, Meta-learning tutorial. International Conference on Artificial Intelligence and Soft Computing. 2010.

Technical reports

  1. Paulson L, Gr¹bczewski K, Mechanizing Set Theory: Cardinal Arithmetic and the Axiom of Choice, Technical Report no. 377, Computer Laboratory, University of Cambridge, UK.