Ondřej Kuželka

I am a postdoc in Steven Schockaert's group (@CS Dept. Cardiff University, since January 2015). Prior to that I was a postdoc supervised by Jan Ramon (@CS Dept. KU Leuven, October 2013 to November 2014). I got my PhD in artificial intelligence from FEE CTU in Prague under supervision of Filip Železný (September 2009 to October 2013).

I currently work at the intersection of machine learning (ML) and knowledge representation (KR). I am also interested in graph mining and its computational complexity, inductive logic programming (ILP), and applications of KR, ML and ILP to computational biology.

KuzelkaO at cs dot cardiff dot ac dot uk

Journal and conference papers

  1. Ondřej Kuželka, Yuyi Wang, Jesse Davis and Steven Schockaert. Relational Marginal Problems: Theory and Estimation. AAAI 2018: 32nd AAAI Conference on Artificial Intelligence, 2018 (Accepted). [arxiv]
  2. Ondřej Kuželka, Jesse Davis and Steven Schockaert. Induction of Interpretable Possibilistic Logic Theories from Relational Data. IJCAI 2017: 26th International Joint Conference on Artificial Intelligence, 2017. [arxiv]
  3. Gustav Šourek, Martin Svatoš, Filip Železný, Steven Schockaert and Ondřej Kuželka. Stacked Structure Learning for Lifted Relational Neural Networks. ILP 2017: Post-proceedings of the 27th International Conference on Inductive Logic Programming 2017 (Best Paper Award). [arxiv]
  4. Ondřej Kuželka, Jesse Davis and Steven Schockaert. Learning Possibilistic Logic Theories from Default Rules. IJCAI 2016: 25th International Joint Conference on Artificial Intelligence, 2016. [pdf] [longer arxiv version]
  5. Ondřej Kuželka, Yuyi Wang and Jan Ramon. Bounds for Learning from Evolutionary-Related Data in the Realizable Case. IJCAI 2016: 25th International Joint Conference on Artificial Intelligence, 2016. [pdf]
  6. Ondřej Kuželka, Jesse Davis and Steven Schockaert. Interpretable Encoding of Densities using Possibilistic Logic. ECAI 2016: 22nd European Conference on Artificial Intelligence, 2016. [pdf]
  7. Gustav Šourek, Suresh Manandhar, Filip Železný, Steven Schockaert and Ondřej Kuželka. Learning Predictive Categories Using Lifted Relational Neural Networks. ILP 2016: Post-proceedings of the 26th International Conference on Inductive Logic Programming 2016. [pdf]
  8. Radomír Černoch, Ondřej Kuželka and Filip Železný. Polynomial and Extensible Solutions in Lock-Chart Solving. Applied Artificial Intelligence 30(10): 923-941, 2016. [online]
  9. Ondřej Kuželka, Jesse Davis and Steven Schockaert. Encoding Markov logic networks in Possibilistic Logic. UAI 2015: Uncertainty in Artificial Intelligence, 2015. [pdf] [online]
  10. Ondřej Kuželka and Jan Ramon. Mine ’Em All: A Note on Mining All Graphs. ILP 2015: Post-proceedings of the 25th International Conference on Inductive Logic Programming 2015. [pdf] [online]
  11. Ondřej Kuželka, Jesse Davis and Steven Schockaert. Constructing Markov Logic Networks from First-Order Default Rules. ILP 2015: Post-proceedings of the 25th International Conference on Inductive Logic Programming 2015. [pdf] [online]
  12. Matěj Holec, Ondřej Kuželka and Filip Železný. Novel Gene Sets Improve Set-Level Classification of Gene Expression Data. BMC Bioinformatics 16: 348, 2015. [online]
  13. Gustav Šourek, Ondřej Kuželka and Filip Železný. Learning to detect network intrusion from a few labeled events and background traffic. AIMS 2015: Autonomous Infrastructure, Management and Security, 2015. [pdf] [online]
  14. Ondřej Kuželka, Andrea Szabóová and Filip Železný, A Method for Reduction of Examples in Relational Learning. Journal of Intelligent Information Systems 42(2): 255-281, 2014. [pdf] [online]
  15. Roman Barták, Radomír Černoch, Ondřej Kuželka and Filip Železný. Formulating the Template ILP Consistency Problem as a Constraint Satisfaction Problem. Constraints 18(2): 144-165, 2013. [online]
  16. Andrea Szabóová, Ondřej Kuželka, Filip Železný and Jakub Tolar. Prediction of DNA-binding proteins from relational features. Proteome Science, 10(1), 66, 2012. [online]
  17. Andrea Szabóová, Ondřej Kuželka, Filip Železný and Jakub Tolar. Prediction of DNA-binding Propensity of Proteins by the Ball-Histogram Method using Automatic Template Search. BMC Bioinformatics, 13, Sup 10, 2012.
  18. Ondřej Kuželka, Andrea Szabóová and Filip Železný. Bounded Least General Generalization. ILP 2012: Inductive Logic Programming, 2012. [pdf] [online]
  19. Ondřej Kuželka, Andrea Szabóová and Filip Železný. Extending the Ball-Histogram Method with Continuous Distributions and an Application to Prediction of DNA-Binding Proteins. BIBM 2012: IEEE International Conference on Bioinformatics and Biomedicine, 2012. [pdf]
  20. Ondřej Kuželka, Andrea Szabóová and Filip Železný. Relational Learning with Polynomials. ICTAI 2012: IEEE International Conference on Tools with Artificial Intelligence, 2012. [pdf]
  21. Ondřej Kuželka and Filip Železný. Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy. Machine Learning 83(2): 163-192, 2011. [pdf] [online]
  22. Ondřej Kuželka, Andrea Szabóová, Matěj Holec and Filip Železný. Gaussian Logic for Predictive Classification. ECML/PKDD 2011: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2011. [pdf] [online]
  23. Ondřej Kuželka, Andrea Szabóová and Filip Železný. Gaussian Logic and Its Applications in Bioinformatics. ACM-BCB 2011: ACM Conference on Bioinformatics, Computational Biology and Biomedicine, 2011. [pdf]
  24. Andrea Szabóová, Ondřej Kuželka, Sergio Morales E., Filip Železný and Jakub Tolar. Prediction of DNA-binding Propensity of Proteins by the Ball-Histogram Method. ISBRA 2011: The 7th International Symposium on Bioinformatics Research and Applications, 2011.[online]
  25. Ondřej Kuželka and Filip Železný. Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples. ILP 2010: Inductive Logic Programming, 2010. [pdf] [online]
  26. Roman Barták, Ondřej Kuželka and Filip Železný. Using Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming. FLAIRS 2010 - Florida Artificial Intelligence Research Society, The 23rd International Conference, 2010.
  27. Filip Železný and Ondřej Kuželka. Taming the Complexity of Inductive Logic Programming (invited talk). SOFSEM 2010: 36th International Conference on Current Trends in Theory and Practice of Computer Science, 2010.
  28. Ondřej Kuželka and Filip Železný. Block-Wise Construction of Acyclic Relational Features with Monotone Irreducibility and Relevancy Properties. ICML 2009: The 26th International Conference on Machine Learning, 2009. [online]
  29. Ondřej Kuželka and Filip Železný. A Restarted Strategy for Efficient Subsumption Testing. Fundamenta Informaticae, 89:95-109, 2008. [pdf]
  30. Ondřej Kuželka and Filip Železný. Fast Estimation of First-Order Clause Coverage through Randomization and Maximum Likelihood. ICML 2008: 25th International Conference on Machine Learning, 2008. [online]

Current and Former Students

  • Martin Svatoš (PhD student working on structure learning for lifted relational neural networks (LRNNs), co-supervised with Filip Železný).
  • Gustav Šourek (PhD student working on lifted relational neural networks (LRNNs) and network security, co-supervised with Filip Železný, previously also my MSc student ).
  • Andrea Fuksová (winner of CISCO outstanding thesis award and Czech and Slovak ACM-SPY thesis competition finalist) .
  • Vojtěch Aschenbrenner (the first incarnation of lifted relational neural networks, LRNNs, appeared in Vojtěch's thesis) .

Lightly refereed papers (workshop…)

  1. Martin Svatoš, Gustav Šourek, Filip Železný, Steven Schockaert and Ondřej Kuželka. Pruning Hypothesis Spaces Using Learned Domain Theories. ILP 2017: Late breaking papers of the 27th International Conference on Inductive Logic Programming 2017. (To appear)
  2. Ondřej Kuželka, Jesse Davis and Steven Schockaert. Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract). NIPS 2016 Workshop on Interpretable Machine Learning in Complex Systems, 2016. [arxiv]
  3. Thomas Ager, Ondřej Kuželka and Steven Schockaert. Inducing symbolic rules from entity embeddings using auto-encoders. NeSy 2016: Proceedings of the 11th International Workshop on Neural-Symbolic Learning and Reasoning. [online]
  4. Gustav Šourek, Vojtěch Aschenbrenner, Filip Železný and Ondřej Kuželka. Lifted Relational Neural Networks. CoCo 2015: Cognitive Computation: Integrating Neural and Symbolic Approaches, 2015. [pdf], [longer arxiv version], [video of Gustav's talk]
  5. Ondřej Kuželka and Jan Ramon. A Note on Restricted Forms of LGG. Late-breaking proceedings of ILP 2015. [pdf] [longer version]
  6. Vojtěch Aschenbrenner and Ondřej Kuželka: Horn-Clause Neural Networks (poster). Spring workshop on Mining and Learning (SML), 2014. [poster]
  7. Gustav Šourek, Ondřej Kuželka and Filip Železný: Predicting Top-k Trends on Twitter using Graphlets and Time Features. ILP 2013: Inductive Logic Programming - Late Breaking Papers, 2013. [pdf]
  8. Andrea Fuksová, Ondřej Kuželka and Andrea Szabóová: A Method for Mining Discriminative Graph Patterns. MLCB 2013: NIPS Machine Learning in Computational Biology Workshop, 2013. [online]
  9. Ondřej Kuželka, Andrea Szabóová and Filip Železný. Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses. Selected papers from the Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2012), 2012. [pdf] [online]
  10. Andrea Szabóová, Ondřej Kuželka and Filip Železný. Prediction of Antimicrobial Activity of Peptides using Relational Machine Learning. IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW 2012), 2012.
  11. Ondřej Kuželka and Filip Železný. An Experimental Evaluation of Lifted Gene Sets. MIND 2011: Workshop on Mining Complex Entities from Network and Biomedical Data, 2011. [pdf]
  12. Ondřej Kuželka, Andrea Szabóová, Matěj Holec and Filip Železný. Gaussian Logic for Proteomics and Genomics. MLSB 2011: the 5th International Workshop on Machine Learning in Systems Biology, 2011. [pdf]
  13. Andrea Szabóová, Ondřej Kuželka, Filip Železný and Jakub Tolar. Prediction of DNA-Binding Proteins from Structural Features. MLSB 2010: Proceedings of the Fourth International Workshop on Machine Learning in Systems Biology, 2010.
  14. Ondřej Kuželka and Filip Železný. Shrinking Covariance Matrices using Biological Background Knowledge. MLSB 2010: Proceedings of the Fourth Workshop on Machine Learning in Systems Biology, 2010. [pdf]
  15. Roman Barták, Ondřej Kuželka and Filip Železný. Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem. AAAI-10 Workshop on Abstraction, Reformulation, and Approximation (WARA-2010), 2010.
  16. Ondřej Kuželka and Filip Železný. Block-Wise Construction of Acyclic Relational Features with Monotone Relevancy. ILP 2009: 19th International Conference on Inductive Logic Programming, 2009
  17. Ondřej Kuželka and Filip Železný. HiFi: Tractable Propositionalization through Hierarchical Feature Construction. ILP 2008: Late Breaking Papers, the 18th International Conference on Inductive Logic Programming, 2008. [pdf]

Misc

TreeLiker software for relational feature construction [link].