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30 papers · 1 filter
Exploiting Transitivity Constraints for Entity Matching in Knowledge Graphs
Jurian Baas, Mehdi Dastani, Ad Feelders
The goal of entity matching in knowledge graphs is to identify entities that refer to the same real-world objects using some similarity metric. The result of entity matching can be…
Sparse Training Theory for Scalable and Efficient Agents
Decebal Constantin Mocanu, Elena Mocanu, Tiago Pinto +5
A fundamental task for artificial intelligence is learning. Deep Neural Networks have proven to cope perfectly with all learning paradigms, i.e. supervised, unsupervised, and reinf…
Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019
Nacira Abbas, Kholoud Alghamdi, Mortaza Alinam +71
One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is…
Necessary and Sufficient Explanations in Abstract Argumentation
AnneMarie Borg, Floris Bex
In this paper, we discuss necessary and sufficient explanations for formal argumentation - the question whether and why a certain argument can be accepted (or not) under various ex…
Transforming Probabilistic Programs for Model Checking
Ryan Bernstein, Matthijs Vákár, Jeannette Wing
Probabilistic programming is perfectly suited to reliable and transparent data science, as it allows the user to specify their models in a high-level language without worrying abou…
Reinforced Anytime Bottom Up Rule Learning for Knowledge Graph Completion
Christian Meilicke, Melisachew Wudage Chekol, Manuel Fink +1
Most of todays work on knowledge graph completion is concerned with sub-symbolic approaches that focus on the concept of embedding a given graph in a low dimensional vector space.…