Reports (Research Report) Year : 2025

2024 Activity Report — Orpailleur Team (LORIA) : Knowledge Discovery and Knowledge Engineering

Abstract

The Orpailleur Team has always advocated for ``Knowledge Discovery guided by Domain Knowledge'', a research line which gained a role of paramount importance in ML and Artificial Intelligence (AI). In particular, the recent seminal paper on ``Interpretable Machine Learning'' lists 10 grand challenges in ML. In these challenges, it can be noticed that knowledge integration in ML is a basic ingredient quite everywhere, while emerging topics are materialized by analogy based reasoning, explainable and trustworthy ML & AI models, in particular, topics pertaining to algorithmic complexity and fairness. These are all represented in the Orpailleur's research program of 2024.

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hal-04971424 , version 1 (28-02-2025)

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  • HAL Id : hal-04971424 , version 1

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Miguel Couceiro, Frédéric Pennerath, Amedeo Napoli, Lydia Boudjeloud-Assala, Brieuc Conan-Guez, et al.. 2024 Activity Report — Orpailleur Team (LORIA) : Knowledge Discovery and Knowledge Engineering. LORIA UMR 7503 CNRS, INRIA, Université de LORRAINE. 2025. ⟨hal-04971424⟩
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