Estevam Rafael Hruschka Junior

estevam at cs dot cmu dot edu

Selected Publications

Journals

  1. Hruschka, E. R. ; Garcia, A. J. T. ; Hruschka JR., ER ; Ebecken, N. F. F. . On the Influence of Imputation in Classification: Practical Issues. Journal of Experimental and Theoretical Artificial Intelligence, 2009.
  2. Hruschka JR., E. R.; Nicoletti, M. C.; Oliveira, V. A.; Bressan GM . BayesRule: a Markov-Blanket based procedure for extracting a set of probabilistic rules from Bayesian classifiers. International Journal of Hybrid Intelligent Systems, v. 5, p. 83-96, 2008.
  3. Cintra, M E ; Camargo, H. A.; Hruschka JR., ER ; Nicoletti, M. C.. Automatic construction of fuzzy rule bases: a further investigation into two alternative inductive approaches. Journal of Universal Computer Science, 2008 (to appear).
  4. Hruschka JR., E. R.; Ebecken, N. F. F., Towards efficient variables ordering for Bayesian Networks Classifier optimization. Data & Knowledge Engineering, v. 63, p. 258-269, 2007.
  5. Hruschka JR., E. R.; Hruschka, E. R.; Ebecken, N. F. F. Bayesian Networks for Imputation in Classification Problems. Journal of Intelligent Information Systems, v. 29, p. 231-252, 2007.
  6. Hruschka JR., E. R., Hruschka, E. R., Ebecken, N. F. F. A Bayesian Imputation Method for a Clustering Genetic Algorithm. Journal of Computational Methods In Sciences And Engineering. IOS Press, 2008 (accepted for publication).
  7. Nicoletti, MC ; Figueira, L. B. ; Hruschka JR., ER . Transferring Neural Network Based Knowledge into an Exemplar-Based Learner. Neural Computing & Applications, v. 16, p. 257-265, 2007.
  8. Hruschka Jr., E. R.; Santos, E. B. Dos ; Galvão, S. D. C. O. An Optimized Evolutionary Conditional Independence Bayesian Classifier Induction Process. Neural Network World - International Journal on Neural and Mass-Parallel Computing and Information Systems, v.16, p. 555-572, 2007.
  9. Hruschka Jr., E. R.; Galvão, S. D. C. O. Fast Conditional Independence-based Bayesian Classifier. Journal of Computing Science and Engineering. , v.1, 162-176, 2007.
  10. Hruschka, E. R., Hruschka JR., ER, Covoes, T. F., Ebecken, N. F. F., Bayesian Feature Selection for Clustering Problems. Journal of Information & Knowledge Management - JIKM. , v.6, p.1 - 13, 2006.
  11. Hruschka JR., E. R., Hruschka, E. R., Ebecken, N. F. F. A Feature Selection Bayesian Approach for Extracting Classification Rules with a Clustering Genetic Algorithm. Applied Artificial Intelligence. London: , v.17, n.5-6, p.489 - 506, 2003.
  12. Hruschka JR., E. R., Ebecken, N. F. F. Missing Values prediction with K2. Intelligent Data Analysis Journal (IDA). Netherlands: , v.6, n.6, p.557 - 566, 2002

Peer Reviewed Conference Papers

  1. CARLSON, A.; BETTERIDGE, J.; WANG, R.; HRUSCHKA JR., ER and MITCHELL, T., Coupled Semi-Supervised Learning for Information Extraction. To appear in the Proceedings of the Third ACM International Conference on Web Search and Data Mining (WSDM), 2010.
  2. CARLSON, A. ; BETTERIDGE, J. ; HRUSCHKA JR., ER ; MITCHELL, T., Coupling Semi-Supervised Learning of Categories and Relations. In: NAACL HLT 2009 Workshop on Semi-supervised Learning for Natural Language Processing, Bouder, 2009.
  3. Santos, E. B. ; Hruschka JR., ER ; Nicoletti, MC . Conditional independence based learning of Bayesian classifiers guided by a variable ordering genetic search. In: The 2007 IEEE Congress on Evolutionary Computation (CEC 2007), 2007, Singapura. Proceedings of The 2007 IEEE Congress on Evolutionary Computation (CEC 2007). Los Alamitos : IEEE Press, 2007. v. 1. p. 1.
  4. Bressan GM ; Oliveira, Vilma Alves de ; Hruschka JR., ER ; Nicoletti, MC . Biomass BasedWeed-crop Competitiveness Classification Using Bayesian Networks. In: The seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007), 2007, Rio de Janeiro. Proceedings of The seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007). Los Alamitos : IEEE Press, 2007. v. 1. p. 1.
  5. Pedro, SDS ; Hruschka JR., ER ; Hruschka, E. R. ; Ebecken, N. F. F. . WNB: a Weighted Naïve Bayesian Classifier. In: The seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007), 2007, Rio de Janeiro. Proceedings of The seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007). Los Alamitos : IEEE Press, 2007. v. 1. p. 1.
  6. Bressan GM, Oliveira, V. A., Hruschka JR., ER, Nicoletti, MC, A Probability Estimation Based Strategy to Optimize the Classification Rule Set Extracted from Bayesian Network Classifiers In: VIII Simp車sio Brasileiro de Automação Inteligente - SBAI 2007, 2007, Florian車polis.  Anais do VIII Simp車sio Brasileiro de Automação Inteligente - SBAI 2007.
  7. Hruschka JR., ER, Santos, E. B., Galvão, S. D. C. O., Variable Ordering in the Conditional Independence Bayesian Classifier Induction Process: An Evolutionary Approach In: 7th International Conference on Hybrid Intelligent Systems, 2007, Kaiserslautern, Los Alamitos: IEEE Press, 2007.
  8. Hruschka JR., ER, Nicoletti, MC, Oliveira, Vilma Alves de, Bressan GM., Markov-Blanket Based Strategy for Translating a Bayesian Classifier into a Reduced Set of Classification Rules In: 7th International Conference on Hybrid Intelligent Systems, 2007, Kaiserslautern, Los Alamitos: IEEE Press, 2007.
  9. Santoro, D. M. ; Nicoletti, MC ; Hruschka JR., ER . C-Focus-3: a C-Focus With a New Heuristic Search Strategy. In: The seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007), 2007, Rio de Janeiro. Proceedings of The seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007). Los Alamitos : IEEE Press, 2007. v. 1. p. 1
  10. Cintra, M E ; Camargo, Heloisa de Arruda ; Hruschka JR., ER ; Nicoletti, MC . Fuzzy Rule Base Generation through Genetic Algorithms and Bayesian Classifiers - a Comparative Approach. In: 7th International Conference on Intelligent Systems Design and Applications (ISDA 2007), 2007, Rio de Janeiro. Proceedings of the 7th International Conference on Intelligent Systems Design and Applications (ISDA 2007). Los Alamitos : IEEE Press, 2007. v. 1. p. 1.
  11. Galvão, S. D. C. O. ; Hruschka JR., ER . A Markov Blanket based strategy to optimize the induction of Bayesian Classifiers when using Conditional Independence Algoritms. In: the 9th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2007), 2007, Rogensburg. Lecture Nontes on Artificial Intelligence. Berlin : Springer, 2007. v. 1. p. 1.
  12. Hruschka JR., ER ; Camargo, H. A.; Cintra, M E ; Nicoletti, M. C.,?BayesFuzzy: using a Bayesian Classifier to Induce a Fuzzy Rule Base. In: IEEE International Conference on Fuzzy Systems - FUZZ-IEEE2007, 2007, Londres. Proceedings of the the Annual IEEE International Conference on Fuzzy Systems. Los Alamitos : IEEE Press, 2007.
  13. Hruschka, E. R. ; Covoes, T. F.; Hruschka JR., E. R. ; Ebecken, N. F. F., Adapting Supervised Feature Selection Methods for Clustering Tasks. In: 2007 Information Resources Management Association International Conference (the 18th Annual IRMA International Conference), Vancouver, Canada, 2007.
  14. Vivencio, D. P., Hruschka JR., E. R., Nicoletti, M. C., dos Santos, E. B. and Galvão, S. D. C. de O. Feature-weighted k-Nearest Neighbor Classifier. In: the first IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2007), Honolulu, Hawaii, 2007.
  15. Yoshida, M. L.; Hruschka JR., ER . Quasi-Incremental Bayesian Classifier. In: ECML/PKDD-2007 International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS-2007), 2007, Vars車via. Proceedings of the ECML/PKDD-2007 International Workshop on Knowledge Discovery from Ubiquitous Data Streams (IWKDUDS-2007). Vars車via : ECML/PKDD, 2007. v. 1. p. 1.
  16. Santos, E. B. Dos ; Hruschka JR., ER . VOGA: Variable Ordering Genetic Algorithm for Learning Bayesian Classifiers. In: 6th International Conference on Hybrid Intelligent Systems - HIS2006, 2006, Auckland. Proceedings of The Sixth International conference on Hybrid Intelligent Systems (HIS06). Los Alamitos CA, USA : IEEE Press, 2006.
  17. Bertini JR, J. R. ; Nicoletti, MC ; Hruschka JR., ER . Two Variants of the Constructive Neural Network Tiling Algorithm. In: 6th International Conference on Hybrid Intelligent Systems - HIS2006, 2006, Auckland. Proceedings of The Sixth International conference on Hybrid Intelligent Systems (HIS06). Los Alamitos CA, USA : IEEE Press, 2006.
  18. Bertini JR, J. R. ; Nicoletti, MC ; Hruschka JR., ER . A Comparative Evaluation of Constructive Neural Networks Methods using PMR and BCP as TLU Training Algorithms. In: IEEE International Conference on Systems, Man, and Cybernetics, 2006, Taipei. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics. Los Alamitos : IEEE Press, 2006
  19. Hruschka, E. R. ; Hruschka JR., E. R. ; Covoes, T. F. ; Ebecken, N. F. F., Feature Selection for Clustering Problems: a Hybrid Algorithm that Iterates Between k-means and a Bayesian Filter. In: HIS05 Fifth International Conference on Hybrid Intelligent Systems, 2005, Rio de Janeiro. Proceedings of The Fifth International conference on Hybrid Intelligent Systems (HIS'05). Los Alamitos CA, USA : IEEE Press, 2005.
  20. Nicoletti, M. C. ; Figueira, L. B. ; Hruschka JR., E. R., Initializing an Exemplar Based Learning Process from a RuleNet Network. In: HIS05 Fifth International Conference on Hybrid Intelligent Systems, 2005, Rio de Janeiro. Proceedings of The Fifth International conference on Hybrid Intelligent Systems (HIS'05).. Los Alamitos, CA, USA : IEEE Press, 2005
  21. Hruschka JR., E. R. ; Hruschka, E. R. ; Ebecken, N. F. F., Applying Bayesian Networks for Meteorological Data Mining. In: The Twenty-fifth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, 2005, Cambridge. APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XIII. Berlin: Springer-Verlag, 2005.
  22. Santoro, D. M. ; Hruschka JR., E. R. ; Nicoletti, M. C., Selecting feature subsets for inducing classifiers using a committee of heterogeneous methods. In: IEEE International Conference on Systems, Man and Cybernetics - SMC, 2005, Hawaii. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (SMC 2005). Los Alamitos , CA : The IEEE Computer Society, 2005.
  23. Hruschka, E. R., Hruschka JR., E. R., Ebecken, N. F. F., Missing Values Imputation for a Clustering Genetic Algorithm. First International Conference on Natural Computation (ICNC'05) and the Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'05), Changsha, China, 2005. Lecture Notes on Computer Science ?LNCS 3612, p. 245-254.
  24. Hruschka JR., E. R., Hruschka, E. R., Ebecken, N. F. F. Feature Selection by Bayesian Networks In: The Seventeenth Canadian Conference on Artificial Intelligence, 2004, London, Ontario. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag, v.3060. p.370 ?379, 2004.
  25. Hruschka, E. R., Hruschka JR., E. R., Ebecken, N. F. F. Towards Efficient Imputation by Nearest-Neighbors: A Clustering-based Approach In: 17th Joint Australian Conference on Artificial Intelligence - AI'04, 2004, Cairns. Lecture Notes in Computer Science (LNAI 3339).. Berlin: Springer-Verlag, v.3339. p.513 ?525, 2004.
  26. Hruschka JR., E. R., Hruschka, E. R., Ebecken, N. F. F. A feature selection Bayesian approach for a clustering genetic algorithm. In: Data Mining IV - Management Information Systems Series - vol. 7 ed.Southampton - UK : WIT Press, 2003.
  27. Hruschka, E. R., Hruschka JR., E. R., Ebecken, N. F. F. A Nearest-Neighbor Method as a Data Preparation Tool for a Clustering Genetic Algorithm In: 18th Brazilian Simposium on Databases (SBBD 2003), 2003, Manaus.?Proceedings of the 18th Brazilian Symposium on Databases / ACM SIGMOD Disk. Manaus: Editora da Universidade Federal do Amazonas, v.1. p.319 ?327, 2003.
  28. Hruschka, E. R., Hruschka JR., E. R., Ebecken, N. F. F. Evaluating a Nearest-Neighbor Method to Substitute Continuous Missing Values In: The 16th Australian Joint Conference on Artificial Intelligence - AI?3, 2003, Perth.?Lecture Notes in Artificial Intelligence (LNAI 2903). p.723 - 734. Heidelberg: Springer-Verlag: Springer-Verlag, v.2903. p.723 ?734, 2003.
  29. Hruschka JR., E. R., Ebecken, N. F. F. Variable Ordering for Bayesian Networks Learning from Data In: International Conference on Computational Intelligence for Modelling, Control and Automation - CIMCA'2003, Vienna, 2003.
  30. Hruschka JR., E. R., Hruschka, E. R., Ebecken, N. F. F. A Feature Selection Bayesian Approach for Extracting Classification Rules with a Clustering Genetic Algorithm In: IEEE International Conference on Data Mining 2002, First Workshop on Data Cleaning and Preprocessing, 2002, Maebashi TERRSA, Maebashi City, 2002.?
  31. Hruschka JR., E. R., Hruschka, E. R., Ebecken, N. F. F. A Data Preparation Bayesian Approach for a Clustering Genetic Algorithm.? In: Frontiers in Artificial Intelligence and Applications, Soft Computing Systems: Design, Management and Applications ed.Amsterdam : IOS Press, v.87, p. 453-461.HIS2002 ?International Conference on Hibrid Intelligent Systems, Chile, 2002.
  32. Hruschka JR., E. R., Ebecken, N. F. F. Ordering attributes for missing values prediction and data classification. In: Data Mining III - Management Information Systems Series - vol. 6 ed.Southampton - UK : WIT Press, Data Mining 2002, Italy, 2002.
  33. Traleski, R., Brito, W., Hruschka JR., E. R. Automação da Criação de Bases de Conhecimento Bayesianas Triangulares. In: Quinto Encontro de Iniciação Cient赤fica da Universidade do Vale do Para赤ba, São Jos?dos Campos, 2001.?
  34. Fialla, A. G., Murai, C. T. V., Piasecki, C., Hruschka JR., E. R. Educação a Distância : Um Estudo de suas Metodologias e Aplicações Pr芍ticas em Curitiba In: XX Congresso da Sociedade Brasileira de Computação, Curitiba, 2000.?
  35. Hruschka JR., E. R., Silva, W. T. Aprendizado e Infer那ncia Bayesiana no Diagn車stico de Doenças Pulmonares In: III Simp車sio Nacional de Inform芍tica, Santa Maria, 1998.

 

Publications - Estevam Rafael Hruschka Junior