• Fast Estimation of First Order Clause Coverage through Randomization and Maximum Likelihood 

      Autor: Kuželka, Ondřej; Železný, Filip
      (2008)
      In inductive logic programming, µ-subsumption is a widely used coveragetest. Unfortunately, testing µ-subsumption is NP-complete, which represents a crucial efficiency bottleneck for many relational learners. In this ...
    • Gaussian Logic for Predictive Classification 

      Autor: Kuželka, Ondřej; Szabóová, Andrea; Holec, Matěj; Železný, Filip
      (2011)
      We describe a statistical relational learning framework called Gaussian Logic capable to work efficiently with combinations of relational and numerical data. The framework assumes that, for a fixed relational structure, ...
    • Prediction of DNA-binding propensity of proteins by the ball-histogram method using automatic template search 

      Autor: Szabóová, Andrea; Kuželka, Ondřej; Železný, Filip; Tolar, Jakub
      (2012)
      We contribute a novel, ball-histogram approach to DNA-binding propensity prediction of proteins. Unlike state-ofthe- art methods based on constructing an ad-hoc set of features describing physicochemical properties of ...
    • Prediction of DNA-binding proteins from relational features 

      Autor: Szabóová, Andrea; Kuželka, Ondřej; Železný, Filip; Tolar, Jakub
      (2012)
      Background: The process of protein-DNA binding has an essential role in the biological processing of genetic information. We use relational machine learning to predict DNA-binding propensity of proteins from their ...
    • A Restarted Strategy for Efficient Subsumption Testing 

      Autor: Kuželka, Ondřej; Železný, Filip
      (2008)
      We study runtime distributions of subsumption testing. On graph data randomly sampled from two different generative models we observe a gradual growth of the tails of the distributions as a function of the problem instance ...