Filip Zelezny
Cited by
Cited by
Comparative evaluation of approaches to propositionalization
MA Krogel, S Rawles, F Železný, PA Flach, N Lavrač, S Wrobel
International Conference on Inductive Logic Programming, 197-214, 2003
Propositionalization-based relational subgroup discovery with RSD
F Železný, N Lavrač
Machine Learning 62 (1-2), 33-63, 2006
RSD: Relational subgroup discovery through first-order feature construction
N Lavrač, F Železný, PA Flach
International Conference on Inductive Logic Programming, 149-165, 2002
Automating knowledge discovery workflow composition through ontology-based planning
M Žáková, P Křemen, F Železný, N Lavrač
IEEE Transactions on Automation Science and Engineering 8 (2), 253-264, 2010
Induction of comprehensible models for gene expression datasets by subgroup discovery methodology
D Gamberger, N Lavrač, F Železný, J Tolar
Journal of biomedical informatics 37 (4), 269-284, 2004
Lattice-search runtime distributions may be heavy-tailed
F Železný, A Srinivasan, D Page
International Conference on Inductive Logic Programming, 333-345, 2002
Lifted relational neural networks
G Sourek, V Aschenbrenner, F Zelezny, O Kuzelka
arXiv preprint arXiv:1508.05128, 2015
Learning relational descriptions of differentially expressed gene groups
I Trajkovski, F Zelezny, N Lavrac, J Tolar
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2007
Block-wise construction of tree-like relational features with monotone reducibility and redundancy
O Kuželka, F Železný
Machine Learning 83 (2), 163-192, 2011
Sequential data mining: A comparative case study in development of atherosclerosis risk factors
J Klema, L Nováková, F Karel, O Stepankova, F Zelezny
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2007
Randomised restarted search in ILP
F Železný, A Srinivasan, CD Page
Machine Learning 64 (1-3), 183-208, 2006
Relational data mining applied to virtual engineering of product designs
M Žáková, F Železný, JA Garcia-Sedano, CM Tissot, N Lavrač, P Křemen, ...
International Conference on Inductive Logic Programming, 439-453, 2006
A restarted strategy for efficient subsumption testing
O Kuželka, F Železný
Fundamenta Informaticae 89 (1), 95-109, 2008
Planning to learn with a knowledge discovery ontology
M Zakova, P Kremen, F Zelezný, N Lavrac
Planning to Learn Workshop (PlanLearn 2008) at ICML 2008, 2008
Lifted relational neural networks: Efficient learning of latent relational structures
G Sourek, V Aschenbrenner, F Zelezny, S Schockaert, O Kuzelka
Journal of Artificial Intelligence Research 62, 69-100, 2018
Comparative evaluation of set-level techniques in predictive classification of gene expression samples
M Holec, J Kléma, F Železný, J Tolar
BMC bioinformatics 13 (S10), S15, 2012
Advancing data mining workflow construction: A framework and cases using the orange toolkit
M Záková, V Podpecan, F Zelezný, N Lavrac
Proc. 2nd Intl. Wshop. Third Generation Data Mining: Towards Service …, 2009
Hifi: Tractable propositionalization through hierarchical feature construction
O Kuzelka, F Zelezný
Inductive Logic Programming, 69, 2008
An experimental test of Occam’s razor in classification
J Zahálka, F Železný
Machine Learning 82 (3), 475-481, 2011
Integrating multiple-platform expression data through gene set features
M Holec, F Železný, J Kléma, J Tolar
International Symposium on Bioinformatics Research and Applications, 5-17, 2009
The system can't perform the operation now. Try again later.
Articles 1–20