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2020 – today
- 2023
[j29]Petr Rysavý
, Filip Zelezný:
Reference-free phylogeny from sequencing data. BioData Min. 16(1) (2023)- [p1]Gustav Sír, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks: From Graphs to Deep Relational Learning. Compendium of Neurosymbolic Artificial Intelligence 2023: 308-336 - 2021
- [j28]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Beyond graph neural networks with lifted relational neural networks. Mach. Learn. 110(7): 1695-1738 (2021) - [c55]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Lossless Compression of Structured Convolutional Models via Lifting. ICLR 2021 - [c54]Jáchym Barvínek, Timothy van Bremen, Yuyi Wang, Filip Zelezný, Ondrej Kuzelka:
Automatic Conjecturing of P-Recursions Using Lifted Inference. ILP 2021: 17-25 - [i8]Matej Uhrín, Gustav Sourek, Ondrej Hubácek, Filip Zelezný:
Optimal sports betting strategies in practice: an experimental review. CoRR abs/2107.08827 (2021) - 2020
- [j27]Frantisek Malinka, Filip Zelezný, Jirí Kléma:
Finding semantic patterns in omics data using concept rule learning with an ontology-based refinement operator. BioData Min. 13(1): 13 (2020) - [j26]Dimitar Kazakov, Filip Zelezný:
Guest editors' introduction: special issue on Inductive Logic Programming (ILP 2019). Mach. Learn. 109(7): 1287-1288 (2020) - [i7]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Beyond Graph Neural Networks with Lifted Relational Neural Networks. CoRR abs/2007.06286 (2020) - [i6]Gustav Sourek, Filip Zelezný:
Lossless Compression of Structured Convolutional Models via Lifting. CoRR abs/2007.06567 (2020) - [i5]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Learning with Molecules beyond Graph Neural Networks. CoRR abs/2011.03488 (2020)
2010 – 2019
- 2019
- [j25]Petr Rysavý, Filip Zelezný:
Estimating sequence similarity from read sets for clustering next-generation sequencing data. Data Min. Knowl. Discov. 33(1): 1-23 (2019) - [j24]Ondrej Hubácek, Gustav Sourek, Filip Zelezný:
Learning to predict soccer results from relational data with gradient boosted trees. Mach. Learn. 108(1): 29-47 (2019) - [j23]Gustav Sourek, Filip Zelezný:
Efficient Extraction of Network Event Types from NetFlows. Secur. Commun. Networks 2019: 8954914:1-8954914:18 (2019) - [c53]Eliska Dvoráková, Sajal Kumar, Jirí Kléma, Filip Zelezný, Karel Drbal, Mingzhou Song:
Evaluating Model-free Directional Dependency Methods on Single-cell RNA Sequencing Data with Severe Dropout. ICBRA 2019: 55-62 - [c52]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Scaling up relational templated neural models. NeSy@IJCAI 2019 - [c51]Martin Svatos, Gustav Sourek, Filip Zelezný:
Revisiting Neural-Symbolic Learning Cycle. NeSy@IJCAI 2019 - 2018
- [j22]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Lifted Relational Neural Networks: Efficient Learning of Latent Relational Structures. J. Artif. Intell. Res. 62: 69-100 (2018) - [c50]Ondrej Hubácek, Gustav Sourek, Filip Zelezný:
Lifted Relational Team Embeddings for Predictive Sports Analytics. ILP Up-and-Coming / Short Papers 2018: 84-91 - [c49]Ondrej Hubácek, Gustav Sourek, Filip Zelezný:
Deep Learning from Spatial Relations for Soccer Pass Prediction. MLSA@PKDD/ECML 2018: 159-166 - 2017
- [c48]Petr Rysavý, Filip Zelezný:
Estimating Sequence Similarity from Contig Sets. IDA 2017: 272-283 - [c47]Jáchym Barvínek, Filip Zelezný:
A First-Order Axiomatization for Transition Learning with Rich Constraints. ILP (Late Breaking Papers) 2017: 1-5 - [c46]Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Stacked Structure Learning for Lifted Relational Neural Networks. ILP 2017: 140-151 - [c45]Martin Svatos, Gustav Sourek, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Pruning Hypothesis Spaces Using Learned Domain Theories. ILP 2017: 152-168 - [i4]Petr Rysavý, Filip Zelezný:
Estimating Sequence Similarity from Read Sets for Clustering Next-Generation Sequencing data. CoRR abs/1705.06125 (2017) - [i3]Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Stacked Structure Learning for Lifted Relational Neural Networks. CoRR abs/1710.02221 (2017) - 2016
- [j21]Radomír Cernoch, Ondrej Kuzelka, Filip Zelezný:
Polynomial and Extensible Solutions in Lock-Chart Solving. Appl. Artif. Intell. 30(10): 923-941 (2016) - [c44]Petr Rysavý, Filip Zelezný:
Estimating Sequence Similarity from Read Sets for Clustering Sequencing Data. IDA 2016: 204-214 - [c43]Gustav Sourek, Suresh Manandhar, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Learning Predictive Categories Using Lifted Relational Neural Networks. ILP 2016: 108-119 - 2015
- [j20]Matej Holec, Ondrej Kuzelka, Filip Zelezný:
Novel gene sets improve set-level classification of prokaryotic gene expression data. BMC Bioinform. 16: 348:1-348:8 (2015) - [j19]David A. Monge, Matej Holec, Filip Zelezný, Carlos García Garino:
Ensemble learning of runtime prediction models for gene-expression analysis workflows. Clust. Comput. 18(4): 1317-1329 (2015) - [c42]Gustav Sourek, Ondrej Kuzelka, Filip Zelezný:
Learning to Detect Network Intrusion from a Few Labeled Events and Background Traffic. AIMS 2015: 73-86 - [c41]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks. CoCo@NIPS 2015 - [i2]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks. CoRR abs/1508.05128 (2015) - 2014
- [j18]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
A method for reduction of examples in relational learning. J. Intell. Inf. Syst. 42(2): 255-281 (2014) - [j17]Fabrizio Riguzzi, Filip Zelezný:
Guest editors introduction: special issue on Inductive Logic Programming (ILP 2012). Mach. Learn. 94(1): 1-2 (2014) - [c40]David A. Monge, Matej Holec, Filip Zelezný, Carlos García Garino:
Ensemble Learning of Run-Time Prediction Models for Data-Intensive Scientific Workflows. CARLA 2014: 83-97 - 2013
- [j16]Roman Barták, Radomír Cernoch, Ondrej Kuzelka, Filip Zelezný:
Formulating the template ILP consistency problem as a constraint satisfaction problem. Constraints An Int. J. 18(2): 144-165 (2013) - [j15]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Data Min. Knowl. Discov. 27(3): 291-293 (2013) - [j14]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Mach. Learn. 93(1): 1-3 (2013) - [c39]Gustav Sourek, Ondrej Kuzelka, Filip Zelezný:
Predicting Top-k Trends on Twitter using Graphlets and Time Features. ILP (Late Breaking Papers) 2013: 52-57 - [e7]Fabrizio Riguzzi, Filip Zelezný:
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 2013 [contents] - [e6]Fabrizio Riguzzi, Filip Zelezný:
Inductive Logic Programming - 22nd International Conference, ILP 2012, Dubrovnik, Croatia, September 17-19, 2012, Revised Selected Papers. Lecture Notes in Computer Science 7842, Springer 2013, ISBN 978-3-642-38811-8 [contents] - [e5]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I. Lecture Notes in Computer Science 8188, Springer 2013, ISBN 978-3-642-40987-5 [contents] - [e4]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II. Lecture Notes in Computer Science 8189, Springer 2013, ISBN 978-3-642-40990-5 [contents] - [e3]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III. Lecture Notes in Computer Science 8190, Springer 2013, ISBN 978-3-642-40993-6 [contents] - 2012
- [j13]Matej Holec, Jirí Kléma, Filip Zelezný, Jakub Tolar:
Comparative evaluation of set-level techniques in predictive classification of gene expression samples. BMC Bioinform. 13(S-10): S15 (2012) - [j12]Andrea Szabóová, Ondrej Kuzelka, Filip Zelezný, Jakub Tolar:
Prediction of DNA-binding propensity of proteins by the ball-histogram method using automatic template search. BMC Bioinform. 13(S-10): S3 (2012) - [c38]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Extending the ball-histogram method with continuous distributions and an application to prediction of DNA-binding proteins. BIBM 2012: 1-4 - [c37]Andrea Szabóová, Ondrej Kuzelka, Filip Zelezný:
Prediction of antimicrobial activity of peptides using relational machine learning. BIBM Workshops 2012: 575-580 - [c36]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Relational Learning with Polynomials. ICTAI 2012: 1145-1150 - [c35]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Bounded Least General Generalization. ILP 2012: 116-129 - [c34]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses. NFMCP 2012: 17-32 - [i1]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
A Revised Publication Model for ECML PKDD. CoRR abs/1207.6324 (2012) - 2011
- [j11]Jan Zahálka, Filip Zelezný:
An experimental test of Occam's razor in classification. Mach. Learn. 82(3): 475-481 (2011) - [j10]Ondrej Kuzelka, Filip Zelezný:
Block-wise construction of tree-like relational features with monotone reducibility and redundancy. Mach. Learn. 83(2): 163-192 (2011) - [j9]Monika Záková, Petr Kremen, Filip Zelezný, Nada Lavrac:
Automating Knowledge Discovery Workflow Composition Through Ontology-Based Planning. IEEE Trans Autom. Sci. Eng. 8(2): 253-264 (2011) - [c33]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Gaussian logic and its applications in bioinformatics. BCB 2011: 496-498 - [c32]Jiri Belohradsky, David A. Monge, Filip Zelezný, Matej Holec, Carlos García Garino:
Template-based semi-automatic workflow construction for gene expression data analysis. CBMS 2011: 1-6 - [c31]Radomír Cernoch, Filip Zelezný:
Subgroup Discovery Using Bump Hunting on Multi-relational Histograms. ILP 2011: 76-90 - [c30]Filip Zelezný:
Satisfiability Machines. ILP (Late Breaking Papers) 2011: 113-120 - [c29]Jirí Kléma, Matej Holec, Filip Zelezný, Jakub Tolar:
Comparative Evaluation of Set-Level Techniques in Microarray Classification. ISBRA 2011: 274-285 - [c28]Andrea Szabóová, Ondrej Kuzelka, Sergio Morales E., Filip Zelezný, Jakub Tolar:
Prediction of DNA-Binding Propensity of Proteins by the Ball-Histogram Method. ISBRA 2011: 358-367 - [c27]Ondrej Kuzelka, Andrea Szabóová, Matej Holec, Filip Zelezný:
Gaussian Logic for Predictive Classification. ECML/PKDD (2) 2011: 277-292 - 2010
- [c26]Roman Barták, Ondrej Kuzelka, Filip Zelezný:
Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem. Abstraction, Reformulation, and Approximation 2010 - [c25]Roman Barták, Ondrej Kuzelka, Filip Zelezný:
Using Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming. FLAIRS 2010 - [c24]Ondrej Kuzelka, Filip Zelezný:
Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples. ILP 2010: 138-145 - [c23]Radomír Cernoch, Filip Zelezný:
Speeding Up Planning through Minimal Generalizations of Partially Ordered Plans. ILP 2010: 269-276 - [c22]Filip Zelezný, Ondrej Kuzelka:
Taming the Complexity of Inductive Logic Programming. SOFSEM 2010: 132-140
2000 – 2009
- 2009
- [j8]Filip Zelezný, Nada Lavrac:
Guest editors' introduction: Special issue on Inductive Logic Programming (ILP-2008). Mach. Learn. 76(1): 1-2 (2009) - [c21]Ondrej Kuzelka, Filip Zelezný:
Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties. ICML 2009: 569-576 - [c20]Matej Holec, Filip Zelezný, Jirí Kléma, Jakub Tolar:
Integrating Multiple-Platform Expression Data through Gene Set Features. ISBRA 2009: 5-17 - [e2]Bettina Berendt, Dunja Mladenic, Marco de Gemmis, Giovanni Semeraro, Myra Spiliopoulou, Gerd Stumme, Vojtech Svátek, Filip Zelezný:
Knowledge Discovery Enhanced with Semantic and Social Information. Studies in Computational Intelligence 220, 2009, ISBN 978-3-642-01890-9 [contents] - 2008
- [j7]Ondrej Kuzelka, Filip Zelezný:
A Restarted Strategy for Efficient Subsumption Testing. Fundam. Informaticae 89(1): 95-109 (2008) - [j6]Jirí Kléma, Lenka Nováková, Filip Karel, Olga Stepánková, Filip Zelezný:
Sequential Data Mining: A Comparative Case Study in Development of Atherosclerosis Risk Factors. IEEE Trans. Syst. Man Cybern. Part C 38(1): 3-15 (2008) - [j5]Igor Trajkovski, Filip Zelezný, Nada Lavrac, Jakub Tolar:
Learning Relational Descriptions of Differentially Expressed Gene Groups. IEEE Trans. Syst. Man Cybern. Part C 38(1): 16-25 (2008) - [c19]Ondrej Kuzelka, Filip Zelezný:
Fast estimation of first-order clause coverage through randomization and maximum likelihood. ICML 2008: 504-511 - [c18]Pavel Smrz, Jana Silhavá, Jirí Kléma, Filip Zelezný:
Gene expression data mining guided by genomic background knowledge. SOFSEM (2) 2008: 101-111 - [e1]Filip Zelezný, Nada Lavrac:
Inductive Logic Programming, 18th International Conference, ILP 2008, Prague, Czech Republic, September 10-12, 2008, Proceedings. Lecture Notes in Computer Science 5194, Springer 2008, ISBN 978-3-540-85927-7 [contents] - 2007
- [c17]Monika Záková, Filip Zelezný:
Exploiting Term, Predicate, and Feature Taxonomies in Propositionalization and Propositional Rule Learning. ECML 2007: 798-805 - 2006
- [j4]Filip Zelezný, Nada Lavrac:
Propositionalization-based relational subgroup discovery with RSD. Mach. Learn. 62(1-2): 33-63 (2006) - [j3]Filip Zelezný, Ashwin Srinivasan, C. David Page Jr.:
Randomised restarted search in ILP. Mach. Learn. 64(1-3): 183-208 (2006) - [c16]Igor Trajkovski, Filip Zelezný, Jakub Tolar, Nada Lavrac:
Relational Subgroup Discovery for Descriptive Analysis of Microarray Data. CompLife 2006: 86-96 - [c15]Aline Paes, Filip Zelezný, Gerson Zaverucha, C. David Page Jr., Ashwin Srinivasan:
ILP Through Propositionalization and Stochastic k-Term DNF Learning. ILP 2006: 379-393 - [c14]Monika Záková, Filip Zelezný, Javier A. García-Sedano, Cyril Masia Tissot, Nada Lavrac, Petr Kremen, Javier Molina:
Relational Data Mining Applied to Virtual Engineering of Product Designs. ILP 2006: 439-453 - [c13]Igor Trajkovski, Filip Zelezný, Nada Lavrac, Jakub Tolar:
Relational Descriptive Analysis of Gene Expression Data. STAIRS 2006: 184-195 - 2005
- [c12]Jan Tozicka, Filip Zelezný, Michal Pechoucek:
Modelling of Agents' Behavior with Semi-collaborative Meta-agents. CEEMAS 2005: 572-575 - [c11]Martin Rehák, Jan Tozicka, Michal Pechoucek, Filip Zelezný, Milan Rollo:
An Abstract Architecture for Computational Reflection in Multi-Agent Systems. IAT 2005: 128-131 - [c10]Filip Zelezný:
Efficient construction of relational features. ICMLA 2005 - [c9]Filip Zelezný:
Efficient Sampling in Relational Feature Spaces. ILP 2005: 397-413 - 2004
- [j2]Dragan Gamberger, Nada Lavrac, Filip Zelezný, Jakub Tolar:
Induction of comprehensible models for gene expression datasets by subgroup discovery methodology. J. Biomed. Informatics 37(4): 269-284 (2004) - [j1]Filip Zelezný:
Efficiency-conscious propositionalization for relational learning. Kybernetika 40(3): 275-292 (2004) - [c8]Nada Lavrac, Filip Zelezný, Saso Dzeroski:
Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. Local Pattern Detection 2004: 71-88 - [c7]Filip Zelezný, Ashwin Srinivasan, David Page:
A Monte Carlo Study of Randomised Restarted Search in ILP. ILP 2004: 341-358 - 2003
- [c6]Mark-A. Krogel, Simon Alan Rawles, Filip Zelezný, Peter A. Flach, Nada Lavrac, Stefan Wrobel:
Comparative Evaluation of Approaches to Propositionalization. ILP 2003: 197-214 - 2002
- [c5]Nada Lavrac, Filip Zelezný, Peter A. Flach:
RSD: Relational Subgroup Discovery through First-Order Feature Construction. ILP 2002: 149-165 - [c4]Filip Zelezný, Ashwin Srinivasan, David Page:
Lattice-Search Runtime Distributions May Be Heavy-Tailed. ILP 2002: 333-345 - [c3]Filip Zelezný, Jirí Zídgek, Olga Stepánková:
A Learning System for Decision Support in Telecommunications. Soft-Ware 2002: 88-101 - 2001
- [c2]Filip Zelezný:
Learning Functions from Imperfect Positive Data. ILP 2001: 248-260 - 2000
- [c1]Filip Zelezný, Petr Miksovský, Olga Stepánková, Jirí Zídek:
ILP for Automated Telephony. ILP Work-in-progress reports 2000
Coauthor Index
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