Vladimir Despotovic: Markov Logic Networks: A step towards interpretable AI

Machine Learning Seminar presentation

Topic: Markov Logic Networks: A step towards interpretable AI

Speaker: Vladimir Despotovic, Faculty of Science, Technology and Medicine; University of Luxembourg

Time: Wednesday, 2021.10.27, 10:00 CET

How to join: Please contact Jakub Lengiewicz

Abstract:

Markov Logic Networks are highly expressive statistical relational models that combine complex relational information expressed by the first-order logic formulas with the uncertainty represented by the use of the undirected probabilistic graphical models (Markov networks). They allow for representation of a relational structure and uncertainty in a very compact manner, leading to human-interpretable models. In this talk we will discuss the theoretical background of the Markov logic networks and showcase the application in the spoken language understanding domain.

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