Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Besold, Tarek R."'
This paper introduces a post-hoc explainable AI method tailored for Knowledge Graph Embedding models. These models are essential to Knowledge Graph Completion yet criticized for their opaque, black-box nature. Despite their significant success in cap
Externí odkaz:
http://arxiv.org/abs/2406.01759
After a surge in popularity of supervised Deep Learning, the desire to reduce the dependence on curated, labelled data sets and to leverage the vast quantities of unlabelled data available recently triggered renewed interest in unsupervised learning
Externí odkaz:
http://arxiv.org/abs/2009.08497
Explainability in Artificial Intelligence has been revived as a topic of active research by the need of conveying safety and trust to users in the `how' and `why' of automated decision-making. Whilst a plethora of approaches have been developed for p
Externí odkaz:
http://arxiv.org/abs/1906.08362
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Besold, Tarek R., Uckelman, Sara L.
The increasing incorporation of Artificial Intelligence in the form of automated systems into decision-making procedures highlights not only the importance of decision theory for automated systems but also the need for these decision procedures to be
Externí odkaz:
http://arxiv.org/abs/1808.07074
Autor:
Besold, Tarek R.
Following an introduction to the context of Human-Level Artificial Intelligence (HLAI) and (computational) analogy research, a formal analysis assessing and qualifying the suitability of the Heuristic-Driven Theory Projection (HDTP) analogy-making fr
Autor:
Besold, Tarek R., Garcez, Artur d'Avila, Bader, Sebastian, Bowman, Howard, Domingos, Pedro, Hitzler, Pascal, Kuehnberger, Kai-Uwe, Lamb, Luis C., Lowd, Daniel, Lima, Priscila Machado Vieira, de Penning, Leo, Pinkas, Gadi, Poon, Hoifung, Zaverucha, Gerson
The study and understanding of human behaviour is relevant to computer science, artificial intelligence, neural computation, cognitive science, philosophy, psychology, and several other areas. Presupposing cognition as basis of behaviour, among the m
Externí odkaz:
http://arxiv.org/abs/1711.03902
We characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algo- rithmic mechanisms; interpretable systems where users can mathemat- ically analyze its algorithmic mechanisms; and co
Externí odkaz:
http://arxiv.org/abs/1710.00794
Autor:
Besold, Tarek R., Garcez, Artur d'Avila, Stenning, Keith, van der Torre, Leendert, van Lambalgen, Michiel
This article aims to achieve two goals: to show that probability is not the only way of dealing with uncertainty (and even more, that there are kinds of uncertainty which are for principled reasons not addressable with probabilistic means); and to pr
Externí odkaz:
http://arxiv.org/abs/1701.05226