Filip Zelezný

101 papers A* 3B 23C 1Misc 1Journal 38Unranked 29

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	An Algorithm to Calculate the J. Comput. Biol. Petr Rysavý, Filip Zelezný
2023	—	`ch.`	Lifted Relational Neural Networks: From Graphs to Deep Relational Learning. Compendium of Neurosymbolic Artificial Intelligence Gustav Sír, Filip Zelezný, Ondrej Kuzelka
2023	J	`jnl`	Reference-free phylogeny from sequencing data. BioData Min. Petr Rysavý, Filip Zelezný
2021	B	`conf`	Automatic Conjecturing of P-Recursions Using Lifted Inference. ILP Jáchym Barvínek, Timothy van Bremen, Yuyi Wang, Filip Zelezný, Ondrej Kuzelka
2021	J	`jnl`	Beyond graph neural networks with lifted relational neural networks. Mach. Learn. Gustav Sourek, Filip Zelezný, Ondrej Kuzelka
2021	A*	`conf`	Lossless Compression of Structured Convolutional Models via Lifting. ICLR Gustav Sourek, Filip Zelezný, Ondrej Kuzelka
2021	J	`jnl`	Optimal sports betting strategies in practice: an experimental review. CoRR Matej Uhrín, Gustav Sourek, Ondrej Hubácek, Filip Zelezný
2020	J	`jnl`	Beyond Graph Neural Networks with Lifted Relational Neural Networks. CoRR Gustav Sourek, Filip Zelezný, Ondrej Kuzelka
2020	J	`jnl`	Finding semantic patterns in omics data using concept rule learning with an ontology-based refinement operator. BioData Min. Frantisek Malinka, Filip Zelezný, Jirí Kléma
2020	J	`jnl`	Guest editors' introduction: special issue on Inductive Logic Programming (ILP 2019). Mach. Learn. Dimitar Kazakov, Filip Zelezný
2020	J	`jnl`	Learning with Molecules beyond Graph Neural Networks. CoRR Gustav Sourek, Filip Zelezný, Ondrej Kuzelka
2020	J	`jnl`	Lossless Compression of Structured Convolutional Models via Lifting. CoRR Gustav Sourek, Filip Zelezný
2019	J	`jnl`	Efficient Extraction of Network Event Types from NetFlows. Secur. Commun. Networks Gustav Sourek, Filip Zelezný
2019	J	`jnl`	Estimating sequence similarity from read sets for clustering next-generation sequencing data. Data Min. Knowl. Discov. Petr Rysavý, Filip Zelezný
2019	—	`conf`	Evaluating Model-free Directional Dependency Methods on Single-cell RNA Sequencing Data with Severe Dropout. ICBRA Eliska Dvoráková, Sajal Kumar, Jirí Kléma, Filip Zelezný, Karel Drbal, Mingzhou Song
2019	J	`jnl`	Learning to predict soccer results from relational data with gradient boosted trees. Mach. Learn. Ondrej Hubácek, Gustav Sourek, Filip Zelezný
2019	—	`conf`	Revisiting Neural-Symbolic Learning Cycle. NeSy@IJCAI Martin Svatos, Gustav Sourek, Filip Zelezný
2019	—	`conf`	Scaling up relational templated neural models. NeSy@IJCAI Gustav Sourek, Filip Zelezný, Ondrej Kuzelka
2018	—	`conf`	Deep Learning from Spatial Relations for Soccer Pass Prediction. MLSA@PKDD/ECML Ondrej Hubácek, Gustav Sourek, Filip Zelezný
2018	J	`jnl`	Lifted Relational Neural Networks: Efficient Learning of Latent Relational Structures. J. Artif. Intell. Res. Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka
2018	—	`conf`	Lifted Relational Team Embeddings for Predictive Sports Analytics. ILP Up-and-Coming / Short Papers Ondrej Hubácek, Gustav Sourek, Filip Zelezný
2017	—	`conf`	A First-Order Axiomatization for Transition Learning with Rich Constraints. ILP (Late Breaking Papers) Jáchym Barvínek, Filip Zelezný
2017	B	`conf`	Estimating Sequence Similarity from Contig Sets. IDA Petr Rysavý, Filip Zelezný
2017	J	`jnl`	Estimating Sequence Similarity from Read Sets for Clustering Next-Generation Sequencing data. CoRR Petr Rysavý, Filip Zelezný
2017	B	`conf`	Pruning Hypothesis Spaces Using Learned Domain Theories. ILP Martin Svatos, Gustav Sourek, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka
2017	B	`conf`	Stacked Structure Learning for Lifted Relational Neural Networks. ILP Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka
2017	J	`jnl`	Stacked Structure Learning for Lifted Relational Neural Networks. CoRR Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka
2016	B	`conf`	Estimating Sequence Similarity from Read Sets for Clustering Sequencing Data. IDA Petr Rysavý, Filip Zelezný
2016	B	`conf`	Learning Predictive Categories Using Lifted Relational Neural Networks. ILP Gustav Sourek, Suresh Manandhar, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka
2016	J	`jnl`	Polynomial and Extensible Solutions in Lock-Chart Solving. Appl. Artif. Intell. Radomír Cernoch, Ondrej Kuzelka, Filip Zelezný
2015	J	`jnl`	Ensemble learning of runtime prediction models for gene-expression analysis workflows. Clust. Comput. David A. Monge, Matej Holec, Filip Zelezný, Carlos García Garino
2015	—	`conf`	Learning to Detect Network Intrusion from a Few Labeled Events and Background Traffic. AIMS Gustav Sourek, Ondrej Kuzelka, Filip Zelezný
2015	—	`conf`	Lifted Relational Neural Networks. CoCo@NIPS Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka
2015	J	`jnl`	Lifted Relational Neural Networks. CoRR Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka
2015	J	`jnl`	Novel gene sets improve set-level classification of prokaryotic gene expression data. BMC Bioinform. Matej Holec, Ondrej Kuzelka, Filip Zelezný
2014	J	`jnl`	A method for reduction of examples in relational learning. J. Intell. Inf. Syst. Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný
2014	—	`conf`	Ensemble Learning of Run-Time Prediction Models for Data-Intensive Scientific Workflows. CARLA David A. Monge, Matej Holec, Filip Zelezný, Carlos García Garino
2014	J	`jnl`	Guest editors introduction: special issue on Inductive Logic Programming (ILP 2012). Mach. Learn. Fabrizio Riguzzi, Filip Zelezný
2013	J	`jnl`	Formulating the template ILP consistency problem as a constraint satisfaction problem. Constraints An Int. J. Roman Barták, Radomír Cernoch, Ondrej Kuzelka, Filip Zelezný
2013	J	`jnl`	Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Data Min. Knowl. Discov. Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný
2013	J	`jnl`	Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Mach. Learn. Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný
2013	B	`ed.`	Inductive Logic Programming - 22nd International Conference, ILP 2012, Dubrovnik, Croatia, September 17-19, 2012, Revised Selected Papers ILP Fabrizio Riguzzi, Filip Zelezný
2013	—	`ed.`	Late Breaking Papers of the 22nd International Conference on Inductive Logic Programming, Dubrovnik, Croatia, September 17-19, 2012 ILP (Late Breaking Papers) Fabrizio Riguzzi, Filip Zelezný
2013	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I ECML/PKDD (1) Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný
2013	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II ECML/PKDD (2) Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný
2013	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III ECML/PKDD (3) Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný
2013	—	`conf`	Predicting Top-k Trends on Twitter using Graphlets and Time Features. ILP (Late Breaking Papers) Gustav Sourek, Ondrej Kuzelka, Filip Zelezný
2012	J	`jnl`	A Revised Publication Model for ECML PKDD CoRR Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný
2012	B	`conf`	Bounded Least General Generalization. ILP Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný
2012	J	`jnl`	Comparative evaluation of set-level techniques in predictive classification of gene expression samples. BMC Bioinform. Matej Holec, Jirí Kléma, Filip Zelezný, Jakub Tolar
2012	—	`conf`	Extending the ball-histogram method with continuous distributions and an application to prediction of DNA-binding proteins. BIBM Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný
2012	J	`jnl`	Prediction of DNA-binding propensity of proteins by the ball-histogram method using automatic template search. BMC Bioinform. Andrea Szabóová, Ondrej Kuzelka, Filip Zelezný, Jakub Tolar
2012	—	`conf`	Prediction of antimicrobial activity of peptides using relational machine learning. BIBM Workshops Andrea Szabóová, Ondrej Kuzelka, Filip Zelezný
2012	—	`conf`	Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses. NFMCP Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný
2012	B	`conf`	Relational Learning with Polynomials. ICTAI Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný
2011	J	`jnl`	An experimental test of Occam's razor in classification. Mach. Learn. Jan Zahálka, Filip Zelezný
2011	J	`jnl`	Automating Knowledge Discovery Workflow Composition Through Ontology-Based Planning. IEEE Trans Autom. Sci. Eng. Monika Záková, Petr Kremen, Filip Zelezný, Nada Lavrac
2011	J	`jnl`	Block-wise construction of tree-like relational features with monotone reducibility and redundancy. Mach. Learn. Ondrej Kuzelka, Filip Zelezný
2011	—	`conf`	Comparative Evaluation of Set-Level Techniques in Microarray Classification. ISBRA Jirí Kléma, Matej Holec, Filip Zelezný, Jakub Tolar
2011	—	`conf`	Gaussian Logic for Predictive Classification. ECML/PKDD (2) Ondrej Kuzelka, Andrea Szabóová, Matej Holec, Filip Zelezný
2011	—	`conf`	Gaussian logic and its applications in bioinformatics. BCB Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný
2011	—	`conf`	Prediction of DNA-Binding Propensity of Proteins by the Ball-Histogram Method. ISBRA Andrea Szabóová, Ondrej Kuzelka, Sergio Morales E., Filip Zelezný, Jakub Tolar
2011	—	`conf`	Satisfiability Machines. ILP (Late Breaking Papers) Filip Zelezný
2011	B	`conf`	Subgroup Discovery Using Bump Hunting on Multi-relational Histograms. ILP Radomír Cernoch, Filip Zelezný
2011	B	`conf`	Template-based semi-automatic workflow construction for gene expression data analysis. CBMS Jiri Belohradsky, David A. Monge, Filip Zelezný, Matej Holec, Carlos García Garino
2010	—	`conf`	Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem. Abstraction, Reformulation, and Approximation Roman Barták, Ondrej Kuzelka, Filip Zelezný
2010	B	`conf`	Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples. ILP Ondrej Kuzelka, Filip Zelezný
2010	B	`conf`	Speeding Up Planning through Minimal Generalizations of Partially Ordered Plans. ILP Radomír Cernoch, Filip Zelezný
2010	B	`conf`	Taming the Complexity of Inductive Logic Programming. SOFSEM Filip Zelezný, Ondrej Kuzelka
2010	Misc	`conf`	Using Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming. FLAIRS Roman Barták, Ondrej Kuzelka, Filip Zelezný
2009	A*	`conf`	Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties. ICML Ondrej Kuzelka, Filip Zelezný
2009	J	`jnl`	Guest editors' introduction: Special issue on Inductive Logic Programming (ILP-2008). Mach. Learn. Filip Zelezný, Nada Lavrac
2009	—	`conf`	Integrating Multiple-Platform Expression Data through Gene Set Features. ISBRA Matej Holec, Filip Zelezný, Jirí Kléma, Jakub Tolar
2009	—	`book`	Knowledge Discovery Enhanced with Semantic and Social Information Bettina Berendt, Dunja Mladenic, Marco de Gemmis, Giovanni Semeraro, Myra Spiliopoulou, Gerd Stumme, Vojtech Svátek, Filip Zelezný
2008	J	`jnl`	A Restarted Strategy for Efficient Subsumption Testing. Fundam. Informaticae Ondrej Kuzelka, Filip Zelezný
2008	A*	`conf`	Fast estimation of first-order clause coverage through randomization and maximum likelihood. ICML Ondrej Kuzelka, Filip Zelezný
2008	—	`conf`	Gene expression data mining guided by genomic background knowledge. SOFSEM (2) Pavel Smrz, Jana Silhavá, Jirí Kléma, Filip Zelezný
2008	B	`ed.`	Inductive Logic Programming, 18th International Conference, ILP 2008, Prague, Czech Republic, September 10-12, 2008, Proceedings ILP Filip Zelezný, Nada Lavrac
2008	J	`jnl`	Learning Relational Descriptions of Differentially Expressed Gene Groups. IEEE Trans. Syst. Man Cybern. Part C Igor Trajkovski, Filip Zelezný, Nada Lavrac, Jakub Tolar
2008	J	`jnl`	Sequential Data Mining: A Comparative Case Study in Development of Atherosclerosis Risk Factors. IEEE Trans. Syst. Man Cybern. Part C Jirí Kléma, Lenka Nováková, Filip Karel, Olga Stepánková, Filip Zelezný
2007	—	`conf`	Exploiting Term, Predicate, and Feature Taxonomies in Propositionalization and Propositional Rule Learning. ECML Monika Záková, Filip Zelezný
2006	B	`conf`	ILP Through Propositionalization and Stochastic k-Term DNF Learning. ILP Aline Paes, Filip Zelezný, Gerson Zaverucha, C. David Page Jr., Ashwin Srinivasan
2006	J	`jnl`	Propositionalization-based relational subgroup discovery with RSD. Mach. Learn. Filip Zelezný, Nada Lavrac
2006	J	`jnl`	Randomised restarted search in ILP. Mach. Learn. Filip Zelezný, Ashwin Srinivasan, C. David Page Jr.
2006	B	`conf`	Relational Data Mining Applied to Virtual Engineering of Product Designs. ILP Monika Záková, Filip Zelezný, Javier A. García-Sedano, Cyril Masia Tissot, Nada Lavrac, Petr Kremen, Javier Molina
2006	—	`conf`	Relational Descriptive Analysis of Gene Expression Data. STAIRS Igor Trajkovski, Filip Zelezný, Nada Lavrac, Jakub Tolar
2006	—	`conf`	Relational Subgroup Discovery for Descriptive Analysis of Microarray Data. CompLife Igor Trajkovski, Filip Zelezný, Jakub Tolar, Nada Lavrac
2005	—	`conf`	An Abstract Architecture for Computational Reflection in Multi-Agent Systems. IAT Martin Rehák, Jan Tozicka, Michal Pechoucek, Filip Zelezný, Milan Rollo
2005	B	`conf`	Efficient Sampling in Relational Feature Spaces. ILP Filip Zelezný
2005	C	`conf`	Efficient construction of relational features. ICMLA Filip Zelezný
2005	—	`conf`	Modelling of Agents' Behavior with Semi-collaborative Meta-agents. CEEMAS Jan Tozicka, Filip Zelezný, Michal Pechoucek
2004	B	`conf`	A Monte Carlo Study of Randomised Restarted Search in ILP. ILP Filip Zelezný, Ashwin Srinivasan, David Page
2004	J	`jnl`	Efficiency-conscious propositionalization for relational learning. Kybernetika Filip Zelezný
2004	J	`jnl`	Induction of comprehensible models for gene expression datasets by subgroup discovery methodology. J. Biomed. Informatics Dragan Gamberger, Nada Lavrac, Filip Zelezný, Jakub Tolar
2004	—	`conf`	Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. Local Pattern Detection Nada Lavrac, Filip Zelezný, Saso Dzeroski
2003	B	`conf`	Comparative Evaluation of Approaches to Propositionalization. ILP Mark-A. Krogel, Simon Alan Rawles, Filip Zelezný, Peter A. Flach, Nada Lavrac, Stefan Wrobel
2002	—	`conf`	A Learning System for Decision Support in Telecommunications. Soft-Ware Filip Zelezný, Jirí Zídgek, Olga Stepánková
2002	B	`conf`	Lattice-Search Runtime Distributions May Be Heavy-Tailed. ILP Filip Zelezný, Ashwin Srinivasan, David Page
2002	B	`conf`	RSD: Relational Subgroup Discovery through First-Order Feature Construction. ILP Nada Lavrac, Filip Zelezný, Peter A. Flach
2001	B	`conf`	Learning Functions from Imperfect Positive Data. ILP Filip Zelezný
2000	—	`conf`	ILP for Automated Telephony. ILP Work-in-progress reports Filip Zelezný, Petr Miksovský, Olga Stepánková, Jirí Zídek