Filip Železný
Dept. of Computer Science
Faculty of Electrical Engineering
Czech Technical University in Prague
Karlovo namesti 13, 12135
Prague 2, Czech Republic
E-mail: zelezny *at* fel.cvut.cz, Phone # +420224357661
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Filip ŽeleznýDept. of Computer Science |
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Publications Šír G.; Železný F.; Kuželka O.: Lifted Relational Neural Networks: from Graphs to Deep Relational Learning. In: A Compendium of Neuro-Symbolic Artificial Intelligence. Amsterdam: IOS Press 2023 (online) Ryšavý P., Železný F.: Reference-Free Phylogeny from Sequencing Data. BMC BioData Mining 16:13, 2023 (online) Ryšavý P., Železný F.: An Algorithm to Calculate the p-value of the Monge-Elkan Distance. ISBRA 2022 (pdf) Svatos M., Jung P., Zelezny F., Marra G., Kuzelka O.: Learning to Generate Molecules From Small Datasets Using Neural Markov Logic Networks. ILP 2022 late-breaking papers, 2022 (pdf) Uhrin M., Sourek G., Hubacek O., Zelezny F.: Optimal sports betting strategies in practice: an experimental review. IMA Journal of Management Mathematics 32:465–489, 2021 (online) Barvinek J., van Bremen T., Wang Y., Zelezny F., Kuzelka O.: Automatic Conjecturing of P-Recursions Using Lifted Inference IJCLR/ILP 2021 (pdf-preprint) Sir G., Zelezny F., Kuzelka O.: Beyond Graph Neural Networks with Lifted Relational Neural Networks. Machine Learning, 110:1695-1738, 2021 (online), also @ AAAI 2023 Journal Track Sourek G., Zelezny F. Lossless Compression of Structured Convolutional Models via Liftings. ICLR 2021: Ninth International Conference on Learning Representations (pdf) Hubacek O., Sourek G., Zelezny F. Forty years of score-based soccer match outcome prediction: an experimental review, IMA Journal of Management Mathematics, 33:1-18, 2021 (online) Malinka F., Zelezny F., Klema J.: Finding semantic patterns in omics data using concept rule learning with an ontology-based refinement operator. BioData Mining, 13, 2020 (online) Sourek G., Zelezny F., Kuzelka O.Learning with Molecules beyond Graph Neural Networks ML4Molecules workshop @ Neurips 2020 (on Arxiv) Zelezny F., Lavrac N.: Guest editors' introduction: Special issue on Inductive Logic Programming (ILP-2019). Machine Learning 109:1287-1288, 2020 (online) Sourek G., Zelezny F.: Efficient extraction of network event types from NetFlows. Security and Communication Networks, 2019 (online Hubacek O., Sourek G., Zelezny F.: Exploiting sports-betting market using machine learning. International Journal of Forecasting 35(2):783-796, 2019 (pdf, online) Hubacek O., Sourek G., Zelezny F.: Learning to predict soccer results from relational data with gradient boosted trees. Machine Learning 108:29-47, 2019 (online) Rysavy P., Zelezny F.: Estimating sequence similarity from read sets for clustering next-generation sequencing data. Data Mining and Knowledge Discovery, 33(1):1-23, 2019 (online, pdf) Zelezny F.: Relational Machine Learning. (Invited Talk) CLA 2018: The 14th Int. Conf. on Concept Lattices and Their Applications (abstract) Dvorakova E., Kumar S., Klema J., Zelezny F., Drbal K., Song M.: Evaluating Model-free Directional Dependency Methods on Single-cell RNA Sequencing Data with Severe Dropout ICBRA 2019 (pdf) Hubacek O., Sourek G., Zelezny F.: Score-based soccer match outcome modeling – an experimental review MathSport 2019 (pdf) Hubacek O., Sourek G., Zelezny F.: Sports betting strategies: an experimental review MathSport 2019 (pdf) Sourek G., Zelezny F., Kuzelka O.: Scaling up relational templated neural models. NeSY 2019 (pdf) Svatos M., Sourek G., Zelezny F.: Revisiting Neural-Symbolic Cycle. NeSY 2019 (pdf) Sourek G., Aschenbrenner V., Zelezny F., Schockaert S., Kuzelka. O: Lifted Relational Neural Networks: Efficient Learning of Latent Relational Structures. Journal of Artificial Intelligence Research 62:69-100, 2018 (online) Hubacek O., Sourek G., Zelezny F.: Deep Learning from Spatial Relations for Soccer Pass Prediction. MLSA 2018 (pdf) Hubacek O., Sourek G., Zelezny F.: Lifted Relational Team Embeddings for Predictive Sport Analytics. ILP 2018 short paper. (pdf) Klema J., Malinka F., Zelezny F.: Semantic biclustering for finding local, interpretable and predictive expression patterns. BMC Genomics, 18(7):41-53, 2017 (online) Sourek G., Svatos M., Zelezny F., Schockaert S., Kuzelka O. Stacked Structure Learning for Lifted Relational Neural Networks. ILP 2017: The 27th International Conference on Inductive Logic Programming. Springer, 2017 (pdf) BEST PAPER AWARD Rysavy P., Zelezny F.: Estimating Sequence Similarity from Contig Sets. IDA 2017, Springer 2017 (pdf) Barvinek J., Zelezny F.: A First-Order Axiomatization for Transition Learning with Rich Constraints. ILP 2017 short paper. (pdf) Svatos M., Sourek G., Zelezny F., Schockaert S., Kuzelka O.: Pruning Hypothesis Spaces Using Learned Domain Theories. ILP 2017 short paper. (pdf) Cernoch R., Kuzelka O., Zelezny F.: Polynomial and Extensible Solutions in Lock-Chart Solving. Applied Artificial Intelligence, 30(10):923-941, 2016 (online) Zelezny F.: Semantic Web and Machine Learning: Time to Re-Sync. (Invited Talk) KESW 2016: Int. Conf. on Knowledge Engineering and Semantic Web (pdf) Rysavy P., Zelezny F. Estimating Sequence Similarity from Read Sets for Clustering Sequencing Data. IDA 2016: The 15th International Symposium on Intelligent Data Analysis. Springer, 2016 (pdf) FRONTIER PRIZE for the best paper of the symposium Sourek G., Manandhar S., Zelezny F., Schockaert S., Kuzelka O.: Learning Predictive Categories Using Lifted Relational Neural Networks. ILP 2016 short paper. (pdf) Holec M., Kuzelka O., Zelezny F.: Novel Gene Sets Improve Set-Level Classification of Prokaryotic Gene Expression Data. BMC Bioinformatics, 16:348, 2015 (online) Sourek G., Aschenbrenner V., Zelezny F., Kuzelka O.: Lifted relational neural networks. CoCo 2015 - NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches. Monge D. A., Holec M., Zelezny F., Garino C.-G.: Ensemble learning of runtime prediction models for gene-expression analysis workflows. Cluster Computing 18:4 1317-29, 2015 (online) Sourek G., Kuzelka O., Zelezny F.:Learning to Detect Network Intrusion from a Few Labeled Events and Background Traffic. AIMS 2015 proceedings, Springer 2015 (online)
Wohlfahrtova M., Brabcova I., Zelezny F., Balaz P., Janousek L., Lodererova A., Honsova E., Wohlfahrt P., and Viklicky O.: Tubular atrophy and low netrin-1 expression leves are risk factors associated with delayed kidney allograft function. Transplantation 97(2):176-183, 2014 (online) Kuzelka O., Szaboova A., Zelezny F.: A Method for Reduction of Examples in Relational Learning. Journal of Intelligent Information Systems 42(2):255-281, 2014 (online, pdf) Zelezny F., Jalovec K., Tolar J.: Learning meets Sequencing: a Generality Framework for Read-Sets. ILP'14 late breaking papers (pdf) Monge D.A., Holec M., Zelezny F., Garino C.G.: Ensemble Learning of Run-Time Prediction Models for Data-Intensive Scientific Workflows. CARLA 2014 proceedings, Springer 2014 (online)
Jalovec K., Zelezny F.: Binary classification of metagenomic samples using discriminative DNA superstrings MLSB'14 (pdf) Sourek G., Kuzelka O., Zelezny F..: Predicting Top-k Trends on Twitter using Graphlets and Time Features. ILP'13 late breaking papers proceedings (pdf) Blockeel H., Kersting K., Nijssen S., Zelezny F.: Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Data Mining and Knowledge Discovery 27(3): 291-293 (2013) Blockeel H., Kersting K., Nijssen S., Zelezny F.: Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Machine Learning 93(1): 1-3 (2013) Riguzzi F., Zelezny F.: Guest editors' introduction: special issue on Inductive Logic Programming. Machine Learning DOI 10.1007/s10994-013-5398-8 (pub ahead of print), 2013 (online) Blockeel H., Kersting K., Nijssen S., Zelezny F.: (Eds.): Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Parts I, II, III. Lecture Notes in Computer Science 8188, Springer 2013 Zelezny F.: Planning to learn: Recent developments and future directions. (Invited Talk) PlanLearn'12: ECAI'12 Workshop on Planning to Learn. (abstract) Bartak R., Cernoch R., Kuzelka O., Zelezny F.: Formulating the Template ILP Consistency Problem as a Constraint Satisfaction Problem. Constraints 18(2):144-165, 2013 (online, pdf) Bartak R., Zelezny F., Kuzelka O.: Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming, In: Encyclopedia of the Sciences of Learning, Springer 2012 (online) Zelezny F., Klema J.: Vyuzivani znalosti v dobyvani znalosti, In: Umela Inteligence VI, Academia 2012 Kuzelka O., Szaboova A., Zelezny F.: Bounded Least General Generalization. ILP 2012 post-conference proceedings, Springer 2013 (online, pdf) Riguzzi F., Zelezny F. (Eds.): Inductive Logic Programming, 22th International Conference, ILP 2012. Springer 2012 (online) Riguzzi F., Zelezny F. (Eds.): Late Breaking Papers of the 22nd International Conference on Inductive Logic Programming, Dubrovnik, Croatia, September 17-19, 2012. CEUR Workshop Proceedings 975, CEUR-WS.org 2012 Szaboova A., Kuzelka O., Zelezny F., Tolar J.: Prediction of DNA-binding Propensity of Proteins by the Ball-Histogram Method using Automatic Template Search BMC Bioinformatics 13(Suppl 10):S3, 2012 (online) Urbanova M., Brabcova I., Girmanova E., Zelezny F., Viklicky O..: Differential Regulation of the Nuclear Factor-kappa-B Pathway by Rabbit Antithymocyte Globulins in Kidney Transplantation. Transplantation 93(6):589-96, 2012 (online) Holec M., Klema J., Zelezny F., Tolar J.: Comparative Evaluation of Set-Level Techniques in Predictive Classification of Gene Expression Samples BMC Bioinformatics 13(Suppl 10):S15, 2012 (online) Szaboova A., Kuzelka O., Zelezny F., Tolar J.: Prediction of DNA-binding proteins from relational features. Proteome Science 10:66, 2012 (online) Blockeel H., Kersting K., Nijssen S., Zelezny F.: A Revised Publication Model for ECML PKDD. CoRR abs/1207.6324, 2012 (online) Kuzelka O., Szaboova A., Zelezny F.: Relational Learning with Polynomials. ICTAI'12: 24th IEEE International Conference on Tools with Artificial Intelligence, 2012 (pdf) Kuzelka O., Szaboova A., Zelezny F.: Extending the Ball-Histogram Method with Continuous Distributions and an Application to Prediction of DNA-Binding Proteins. BIBM'2012: 2012 IEEE International Conference on Bioinformatics and Biomedicine (pdf) Szaboova A., Kuzelka O., Zelezny F.: Prediction of Antimicrobial Activity of Peptides using Relational Machine Learning, IEEE BIBM 2012 International Workshop on Computational Proteomics, 2012 (pdf) Kuzelka O., Szaboova A., Zelezny F.: Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses, NFCMP'12: Proceedings of the ECML/PKDD'12 Workshop on New Frontiers In Mining Complex Patterns, Springer 2012 (online, pdf) Kuzelka O., Szaboova A., Holec M., Zelezny F. Gaussian Logic for Predictive Classification. ECML/PKDD 2011: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Springer 2011 (online, pdf) Zahalka J., Zelezny F.: An Experimental Test of Occam's Razor in Classification (Technical note). Machine Learning 82(3):475-481, 2011 (online, pdf) Zakova M., Kremen P., Zelezny F., Lavrac N.: Automatic Knowledge Discovery Workflow Composition through Ontology-Based Planning. IEEE Trans. Autom. Sci. and Eng. 8(2):253-264, 2011 (online, pdf) Kuzelka O., Zelezny F.: Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy. Machine Learning 83(2):163-192, 2011 (online, pdf) Cernoch R., Zelezny F.: Subgroup Discovery using Bump Hunting on Multi-Relational Histograms. ILP 2011: 21th International Conference on Inductive Logic Programming, Springer 2011 (online, pdf) Szaboova A., Kuzelka O., Morales S.E., Zelezny F., Tolar J: Prediction of DNA-binding Propensity of Proteins by the Ball-Histogram Method. ISBRA 2011: the 7th International Symposium on Bioinformatics Research and Applications, Springer 2011 (pdf) Klema J., Holec M., Zelezny F., Tolar J.: Comparative Evaluation of Set-Level Techniques in Microarray Classification. ISBRA 2011: the 7th International Symposium on Bioinformatics Research and Applications, Springer 2011 (pdf) Zelezny F.: Satisfiability Machines. ILP 2011: 21th International Conference on Inductive Logic Programming, Late-breaking Proceedings (pdf) Kuzelka O., Zelezny F. An Experimental Evaluation of Lifted Gene Sets MIND 2011: ECML/PKDD 2011 Workshop on Mining Complex Entities from Network and Biomedical Data (Athens 9/11). (pdf) Szaboova A., Kuzelka O., Zelezny F. Gaussian Logic and Its Applications in Bioinformatics (poster paper). ACM-BCB 2011: ACM Conference on Bioinformatics, Computational Biology and Biomedicine (Chicago 8/11). (pdf) Szaboova A., Kuzelka O., Zelezny F., Tolar J. Prediction of DNA-binding Propensity of Proteins Using Distributions of Charged Amino Acids in Primary Structure (poster). ACM-BCB 2011: ACM Conference on Bioinformatics, Computational Biology and Biomedicine (Chicago 8/11). (pdf) Monge D., Belohradsky J., Garcia C.-G., Zelezny F.: A Performance Prediction Module for Workflow Scheduling. HPC'2011: 4th Symposium on High-Performance Computing in Latin America (Cordoba 8/11). (pdf) Kuzelka O., Szaboova A., Holec M., Zelezny F. Gaussian Logic for Proteomics and Genomics MLSB 2011: the 5th International Workshop on Machine Learning in Systems Biology (Vienna 7/11). (pdf) Belohradsky J., Monge D., Zelezny F., Holec M., Garion C.-G.: Template-Based Semi-Automatic Workflow Construction for Gene Expression Data Analysis (poster paper) CBMS 2011: the 24th INternational Symposium on Computer-Based Medical Systems (Bristol 6/11). (pdf) Szaboova A., Kuzelka O., Zelezny F., Tolar J. Searching for Important Amino Acids in DNA-binding Proteins for Histogram Methods (poster paper). ISBRA 2011: the 7th International Symposium on Bioinformatics Research and Applications (Changsha 5/11). (pdf) Cernoch R., Zelezny F. Probabilistic Rule Learning through Integer Linear Programming. Znalosti 2011 10th Czech-Slovak Conference on Knowledge Management. (pdf) Zelezny F., Kuzelka F.: Taming the Complexity of Inductive Logic Programming (Invited Talk) SOFSEM 2010: 36th Int. Conf. on Current Trends in Theory and Practice of Computer Science(online, pdf slides) Cernoch R., Zelezny F.: Speeding up Planning through Minimal Generalizations of Partially Ordered Plans. ILP 2010: 20th International Conference on Inductive Logic Programming, Springer 2010 (online, pdf) Kuzelka O., Zelezny F.Shrinking Covariance Matrices Using Biological Background Knowledge. MLSB 2010: 4th International Workshop on Machine Learning in Systems Biology (Edinburgh 10/10). (pdf) Szaboova A., Kuzelka O., Zelezny F., Tolar J. Prediction of DNA-Binding Proteins from Structural Features. MLSB 2010: 4th International Workshop on Machine Learning in Systems Biology (Edinburgh 10/10). (pdf) Szaboova A., Kuzelka O., Zelezny F., Tolar J.: Mining Frequent Spatial Docking Patterns in Zinc Finger - DNA Complexes. ESBME 2010: 7th European Symposium on Biomedical Engineering (Chalkidiki 5/10). (pdf) Kuzelka O., Zelezny F.: Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples. ILP 2010: 20th International Conference on Inductive Logic Programming (Firenze 6/10). To appear in Springer LNCS. (pdf) Bartak R., Kuzelka O., Zelezny F.: Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem. WARA 2010 AAAI 2010 workshop on Abstraction, Reformulation, and Approximation (Atlanta 7/10) (pdf) Holec M., Zelezny F., Klema J., Tolar. J.: A Comparative Evaluation of Gene Set Analysis Techniques in Predictive Classification of Expression Samples International Conference on Bioinformatics, Computational Biology, Genomics and Chemoinformatics (BCBGC-2010) (pdf) Bartak R., Kuzelka O., Zelezny F.: Using Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming FLAIRS-23 - Florida Artificial Intelligence Research Society, The 23rd International Conference, 2010 (pdf) Kuzelka O., Zelezny F.: A Restarted Strategy for Efficient Subsumption Testing. Fundamenta Informaticae 89(1):95-109, 2008 (online, pdf) Zelezny F., Lavrac N.: Guest editors' introduction: Special issue on Inductive Logic Programming (ILP-2008). Machine Learning 76(1):1-2, 2009 (online, pdf) Klema, J., Zelezny, F., Trajkovski, I., Karel, F., Cremilleux, B. and Tolar, J.: Gene Expression Mining Guided by Background Knowledge. In: Data Mining and Medical Knowledge Management: Cases and Applications, IGI Global 2009. Kuzelka O., Zelezny F.: Block-Wise Construction of Acyclic Relational Features with Monotone Irreducibility and Relevancy Properties. ICML 2009: the 26th International Conference on Machine Learning (pdf) Holec M., Zelezny F., Klema J., Tolar J.: Integrating Multiple-Platform Expression Data through Gene Set Features. ISBRA 2009: the 5th International Symposium on Bioinformatics Research and Applications, Springer 2009. (pdf) Holec M., Klema J., Zelezny F., Belohradsky J., Tolar. J.: Cross-Genome Knowledge-Based Expression Data Fusion International Conference on Bioinformatics, Computational Biology, Genomics and Chemoinformatics (BCBGC-09) Kuzelka O., Zelezny F.: Block-Wise Construction of Acyclic Relational Features with Monotone Relevancy. ILP 2009: 19th International Conference on Inductive Logic Programming, 2009 Zakova M, Podpecan V., Zelezny F., Lavrac N.: Advancing Data Mining Workflow Construction: A Framework and Cases using the Orange Toolkit SoKD: ECML/PKDD 2009 workshop on Third Generation Data Mining: Towards Service oriented Knowledge Discovery Berendt B., Mladenic D., de Gemmis M., Semeraro G., Spiliopoulou M., Stumme G., Svatek V., Zelezny F. (editors): Knowledge Discovery Enhanced with Semantic and Social Information , Springer 2009 Zelezny F., Lavrac N. (Eds.): Inductive Logic Programming, 18th International Conference, ILP 2008. Springer 2008 (online) Kuzelka O., Zelezny F.: Fast Estimation of First-Order Clause Coverage through Randomization and Maximum Likelihood. ICML 2008: the 25th International Conference on Machine Learning (pdf) Klema J., Novakova L., Karel F., Stepankova O., Zelezny F.: Sequential Data Mining: A Comparative Case Study in Development of Atherosclerosis Risk Factors . IEEE Trans. Sys Man Cyb C 38(1):3-15, 2008 (online) Trajkovski I., Zelezny F., Lavrac N., Tolar J.: Learning Relational Descriptions of Differentially Expressed Gene Groups . IEEE Trans. Sys Man Cyb C 38(1):16-25, 2008 (online, pdf) Zakova M., Kremen P., Zelezny F., Lavrac N.: Using Ontological Reasoning and Planning for Data Mining Workflow Composition SoKD: ECML/PKDD 2008 workshop on Third Generation Data Mining: Towards Service oriented Knowledge Discovery Zakova M., Kremen P., Zelezny F., Lavrac N.: Planning to Learn with a Knowledge Discovery Ontology Planning to Learn Workshop at ICML 2008 Kuzelka O., Zelezny F.: HiFi: Tractable Propositionalization through Hierartchical Feature Construction Late-breaking papers, ILP 2008: 18th International Conference on Inductive Logic Programming. Moulik K., Zelezny F.: Predicting Gene-Coexpression from Pathway Relations Late-breaking papers, ILP 2008: 18th International Conference on Inductive Logic Programming. Holec M., Zelezny F., Klema J., Svoboda J., Tolar J.: Using Bio-Pathways in Relational Learning. Late-breaking papers, ILP 2008: 18th International Conference on Inductive Logic Programming. Klema J., Silhava J, Smrz P., Zelezny F.: Gene expression data mining guided by genomic background knowledge. In SOFSEM'08: Current Trends in Theory and Practice of Computer Science, 2008. Zelezny F. : O empirickem vyzkumu algoritmickeho objevovani. In: Umela Inteligence V, Academia, Prague 2007 (In Czech) Zakova M., Zelezny F.: Exploiting Term, Predicate, and Feature Taxonomies in Propositionalization and Propositional Rule Learning. ECML/PKDD 2007: 18th European Conference on Machine Learning / 11th European Conference on Principles and Practice of Knowledge Discovery, Springer 2007 (pdf) Zakova, M. - Zelezny, F. - Kremen, P. - Tissot, C.M. - Lavrac, N.: Relational Data Mining through Propositionalization and Subsequent Propositional Search for Semantic Virtual Engineering. In KCAP 2007 Workshop on Knowledge Management and Semantic Web for Engineering Design (KW4ED�07). New York: ACM, 2007 Kuzelka O., Zelezny F.: A Restart Strategy for Fast Subsumption Check and Coverage Estimation. 6th Workshop on Multi-Relational Data Mining (MRDM'07) at ECML/PKDD'07 (pdf) Zakova M., Zelezny F.: Exploiting Taxonomic Background Knowledge in Propositionalization and Rule Learning. ECML/PKDD'07 workshop on Prior Conceptual Knowledge in Machine Learning (PriCKL'07), extended version of an ECML/PKDD'07 paper (pdf) Zakova M., Kremen P., Garcia-Sedano, J. A., Tissot C. M., Lavrac N., Zelezny F., Molina J.: Relational Pattern and Subgroup Discovery in CAD Documents. Znalosti 2007 - Sborn�k p��sp�vk� 6. ro�n�ku konference, 2007. (pdf) Zakova M., Zelezny F., Garcia-Sedano, J. A., Tissot C. M., Lavrac N., Kremen P., Molina J.: Relational Data Mining Applied to Virtual Engineering of Product Designs. ILP 2006: 16th International Conference on Inductive Logic Programming. Springer 2007 (pdf) Paes A., Zelezny F., Zaverucha G., Page D., Srinivasan A.: ILP Through Propositionalization and Stochastic k-Term DNF Learning. ILP 2006: 16th International Conference on Inductive Logic Programming. Springer 2007 (pdf) Zelezny F., Srinivasan A., Page D.: Randomized Restarted Search in ILP. Machine Learning 64(1-2):183--208, 2006 (online, pdf) Zelezny F., Lavrac N.: Propositionalization-Based Relational Subgroup Discovery with RSD. Machine Learning 62(1-2):33-63, 2006 (online, pdf) Trajkovski I., Zelezny F., Tolar J., Lavrac N.: Relational Subgroup Discovery for Descriptive Analysis of Microarray Data. CompLife 2006: 2nd International Symposium on Computational Life Science. Springer 2006 (pdf) Zakova M., Zelezny F., Garcia-Sedano J., Tissot C. M., Lavrac N.: Relational Data Mining Applied to Virtual Engineering of Product Designs. 16th Int. Conf. on Inductive Logic Programming - Short Papers. Santiago de Compostela 8/2006 (pdf, ppt slides, ppt slides) Paes A., Zelezny F., Zaverucha G., Page D., Srinivasan A.: ILP through Propositionalization and Stochastic k-term DNF Learning. 16th Int. Conf. on Inductive Logic Programming - Short Papers. Santiago de Compostela 8/2006 (pdf, ppt slides) Trajkovski I., Zelezny F., Tolar J., Lavrac N.: Relational Descriptive Analysis of Gene Expression Data. STAIRS-2006 (3rd European Starting AI Researcher Symposium) at the 17th European Conference on Artificial Intelligence. Riva del Garda 8/2006. (pdf) Zelezny F., Tolar J., Lavrac N., Stepankova O.: Summarizing gene-expression-based classifiers by meta-mining comprehensible relational patterns. BioMED 2006: The Fourth IASTED International Conference on Biomedical Engineering. Innsbruck 2/2006. (pdf) Zelezny F.: Efficient Sampling in Relational Feature Spaces. ILP 2005: 15th International Conference on Inductive Logic Programming, Springer 2005 (pdf) Rehak M., Tozicka J., Pechoucek M., Zelezny F.: An Abstract Architecture for Computational Reflection in Multi-Agent Systems. The 2005 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (pdf) Zelezny F.: Efficient Construction of Relational Features. ICMLA 2005: 4th International Conference on Machine Learning and Applications. IEEE Computer Society Press 2005 (pdf) Zelezny F., Tolar J., Lavrac N., Stepankova O.: Relational Subgroup Discovery for Gene Expression Data Mining. EMBEC'05: the 3rd European Medical & Biological Engineering Conf. / IFMBE European Conf. on Biomedical Engineering. Prague 11/2005. (pdf) Zelezny F.: Relationalization: a Framework for Reconstructing Structures from Propositional Descriptions Work-in-Progress Track of the 15th Int. Conf. on Inductive Logic Programming. Bonn 2005 (pdf) Zelezny F.: How Computers Discover How Computers Discover (a mini-review of algorithmic meta-discovery). In Procs of the Czech-Argentine Biennale "e-Golems" (Interdisciplinary aspects of Human-Machine Co-existence and Co-operation). CTU Press, Prague 7/2005. (fulltext in pdf, presentation slides in pdf) Klema J., Holas T., Karel F., Zelezny F.: Mining the Strongest Patterns In Medical Sequential Data. 3rd European Medical & Biological Engineering Conf. / IFMBE European Conf. on Biomedical Engineering. Prague 11/2005. Tozicka J., Zelezny F., Pechoucek M.: Modelling of Agents' Behavior with Semi-Collaborative Meta-Agents. Short paper at the 4th Int. Central and Eastern European Conf. on Multi-Agent Systems (CEEMAS'05), Budapest, Hungary 9/2005. To appear. Zelezny F.: Analyza genomickych dat algoritmy strojoveho uceni. Konference Telemedicina Brno, 2005 Zelezny F.: Tractable construction of relational features. Znalosti '05, Bratislava 2/2005 (fulltext in pdf) Zelezny F., Srinivasan A., Page D.: A Monte Carlo Study of Randomised Restarted Search in ILP . ILP 2004: 14th International Conference on Inductive Logic Programming, Springer 2004 (fulltext in pdf, presentation in pdf) Gamberger D., Lavrac N., Zelezny F., Tolar J.: Induction of comprehensible models for gene expression datasets by subgroup discovery methodology. Journal of Biomedical Informatics 37(4):269-284, 2004. (online, pdf) Zelezny F.: Efficiency-conscious Propositionalization for Relational Learning Kybernetika 4(3):275-292, 2004 (online, pdf) Zelezny F.: A Bottom Set Strategy For Tractable Feature Construction. Work-in-Progress Track of the 14th Int. Conf. on Inductive Logic Programming. Porto 2004 (fulltext in pdf, presentation in pdf) Lavrac N., Zelezny F., Dzeroski S.: Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. In: Boulicaut J.F., Morik K., Siebes A.: Detecting Local Patterns - seminar Proceedings. Dagstuhl 4/2004, Springer-Verlag, 2004. (postscript) Gamberger D., Lavrac N., Zelezny F., Tolar J.: Induction of comprehensible models for gene expression datasets by subgroup discovery methodology. In 2nd EUNITE Workshop on Intelligent Technologies for GeneExpression Based Individualized Medicine. Jena: BioControl Jena GmbH, 2004 Zelezny F., Klema J., Stepankova O.: Strojove uceni v dobyvani znalosti. In: Umela Inteligence IV, Academia, Prague 2003 (In Czech) Krogel M., Rawles S., Zelezny F., Flach P., Lavrac N., Wrobel S.: Comparative Evaluation of Approaches to Propositionalization. ILP 2003: 13th International Conference on Inductive Logic Programming, Springer 2003 (pdf) Zelezny F., Srinivasan A., Page D.: Lattice-Search Runtime Distributions May Be Heavy-Tailed. ILP 2002: 12th International Conference on Inductive Logic Programming, Springer 2003 (pdf) Lavrac N., Zelezny F., Flach P.: RSD: Relational Subgroup Discovery through First-order Feature Construction. ILP 2002: 12th International Conference on Inductive Logic Programming, Springer 2003 (pdf) Zelezny F., Lavrac N., Dzeroski S.: Constraint-Based Relational Subgroup Discovery. Workshop on Multirelational Data Mining (MRDM 03) at KDD 03, Washington DC, 2003.(pdf) Zelezny F., Lavrac N., Dzeroski S.: Using Constraints in Relational Subgroup Discovery (extended abstract) . Int. Conf. on Methodology & Statistics, Ljubljana 9/2003. Zelezny F., Stepankova O.: Efektivni prevod multirelacni databaze na jednorelacni reprezentaci (in Czech). In: V. Svatek (ed.): Znalosti 2003 (2st national conference), Ostrava, Czech Rep., 2/2003 Klema, J., Zelezny, F. Data-Mining and Decision-Support Systems Integration. In: Proceedings of Workshop 2003. Prague : CTU, 2003, vol. A, p. 228-229. ISBN 80-01-02708-2. Zelezny F., Zidek J., Stepankova O.: A Learning System for Decision Support in Telecommunications. In: Bustard D., Weiru L., Sterritt R. (eds.): Soft-Ware 2002 Computing in an Imperfect World, 1st Int. Conference, Belfast, Northern Ireland, 4/2002. Springer-Verlag 2002, ISBN 3-540-43481-X. (pdf, ppt slides) Aubrecht P., Zelezny F., Miksovsky P., Stepankova O.: SumatraTT: Towards a Universal Data Preprocessor. In: Proceedings of the 16th European Meeting on Cybernetics and System Research, vol. 2, p. 818-823. Vienna, Austria, 4/2002, Austrian Society for Cybernetics Studies, ISBN 3-85206-160-1. (BEST PAPER AWARD). Cestnik B., Lavrac N., Zelezny F., Gamberger D., Todorovski L., Kline M.: Data Mining for Decision Support in Marketing: A Case Study in Targeting a Marketing Campaign. In: IDDM-2002 workshop at ECML'02, Helsinki, Finland 2002. Zelezny F.: Learning Functions from Imperfect Positive Data. ILP 2001: 11th International Conference on Inductive Logic Programming, Springer 2001 (pdf, postscript) Zelezny F., Miksovsky P., Stepankova O., Zidek J.: ILP for automated telephony. In: Cussens J., Frisch A. (eds.): Proceedings of the work-in-progress track of the 10th Intermational Conference on Inductive Logic Programming (ILP 2000), Imperial College, London, UK, 6/2000. |
