50 citations · 73 across the 4 of their papers we have counts for
4 papers
Uncertainty Quantification as a Principled Foundation for Explainable Artificial Intelligence: A Case Study of Counterfactual Explanations
Kacper Sokol, Santo M. A. R. Thies, Eyke Hüllermeier
In this paper we argue that, to its detriment, transparency research overlooks many foundational concepts of artificial intelligence. As an illustrating example we focus on uncerta…
Towards Green Automated Machine Learning: Status Quo and Future Directions
Tanja Tornede, Alexander Tornede, Jonas Hanselle +3
Automated machine learning (AutoML) strives for the automatic configuration of machine learning algorithms and their composition into an overall (software) solution - a machine lea…
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model
Julian Lienen, Eyke Hüllermeier, Ralph Ewerth +1
In many real-world applications, the relative depth of objects in an image is crucial for scene understanding. Recent approaches mainly tackle the problem of depth prediction in mo…
Preference-based Online Learning with Dueling Bandits: A Survey
Viktor Bengs, Robert Busa-Fekete, Adil El Mesaoudi-Paul +1
In machine learning, the notion of multi-armed bandits refers to a class of online learning problems, in which an agent is supposed to simultaneously explore and exploit a given se…