63.6k citations · 68k across the 67 of their papers we have counts for
Showing 2016 · stat.MLShow all
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stat.ML2016★ 87 cited
Learning to Pivot with Adversarial Networks
Gilles Louppe, Michael Kagan, Kyle Cranmer
Several techniques for domain adaptation have been proposed to account for differences in the distribution of the data used for training and testing. The majority of this work focu…
stat.ML2016★ 2 cited
Context-dependent feature analysis with random forests
Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu +2
In many cases, feature selection is often more complicated than identifying a single subset of input variables that would together explain the output. There may be interactions tha…