Can I read Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract) on EtoBox?

Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract) by Kuzelka, Ondrej; Davis, Jesse; Schockaert, Steven is a scholarly article available to read on EtoBox.

What is Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract) about?

In this paper, we advocate the use of stratified logical theories for representing probabilistic models. We argue that such encodings can be more interpretable than those obtained in existing frameworks such as Markov logic networks. Among others, this allows for the use of domain experts to improve learned models by directly removing, adding, or modifying logical formulas.

Author

Kuzelka, Ondrej; Davis, Jesse; Schockaert, Steven

Published

2016

Language

EN