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Henri Prade

5 accepted papers

2026

A Survey on Quantitative Possibility Theory in Artificial Intelligence. A Convenient Uncertainty and Preference Model

IJCAI 2026

Quantitative (or numerical) possibility theory offers a simple but yet very expressive setting for handling higher-order uncertainty and in particular imprecise probabilities. The paper surveys the basic ideas and notions underlying numerical possibility theory, its relation to the other uncertainty

Cited by 0Scholar
2015

Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees

ICML 2015poster

Entropy gain is widely used for learning decision trees. However, as we go deeper downward the tree, the examples become rarer and the faithfulness of entropy decreases. Thus, misleading choices and over-fitting may occur and the tree has to be adjusted by using an early-stop criterion or post pruni…

Cited by 19SourcePDFScholar