45 citations · 93 across the 6 of their papers we have counts for
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stat.ML2020★ 45 cited
Interpretable Random Forests via Rule Extraction
Clément Bénard, Gérard Biau, Sébastien da Veiga +1
We introduce SIRUS (Stable and Interpretable RUle Set) for regression, a stable rule learning algorithm which takes the form of a short and simple list of rules. State-of-the-art l…
stat.ML2018★ 39 cited
Global sensitivity analysis for optimization with variable selection
Adrien Spagnol, Rodolphe Le Riche, Sebastien Da Veiga
The optimization of high dimensional functions is a key issue in engineering problems but it frequently comes at a cost that is not acceptable since it usually involves a complex a…