10 citations · 22 across the 11 of their papers we have counts for
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stat.ML2022★ 10 cited
PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through Supermartingales
Maxime Haddouche, Benjamin Guedj
While PAC-Bayes is now an established learning framework for light-tailed losses (\emph{e.g.}, subgaussian or subexponential), its extension to the case of heavy-tailed losses rema…
cs.LG2022★ 2 cited
Online PAC-Bayes Learning
Maxime Haddouche, Benjamin Guedj
Most PAC-Bayesian bounds hold in the batch learning setting where data is collected at once, prior to inference or prediction. This somewhat departs from many contemporary learning…