activity
20192021
most citedOn strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables

18 citations · 19 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2021

Shapley values for feature selection: The good, the bad, and the axioms

Daniel Fryer, Inga Strümke, Hien Nguyen

The Shapley value has become popular in the Explainable AI (XAI) literature, thanks, to a large extent, to a solid theoretical foundation, including four "favourable and fair" axio…

stat.AP20201 cited

SARGDV: Efficient identification of groundwater-dependent vegetation using synthetic aperture radar

Mason Terrett, Daniel Fryer, Tanya Doody +2

Groundwater depletion impacts the sustainability of numerous groundwater-dependent vegetation (GDV) globally, placing significant stress on their capacity to provide environmental…

stat.ML2020

Explaining the data or explaining a model? Shapley values that uncover non-linear dependencies

Daniel Vidali Fryer, Inga Strümke, Hien Nguyen

Shapley values have become increasingly popular in the machine learning literature thanks to their attractive axiomatisation, flexibility, and uniqueness in satisfying certain noti…

stat.ME2020

Shapley value confidence intervals for attributing variance explained

Daniel Fryer, Inga Strumke, Hien Nguyen

The coefficient of determination, the , is often used to measure the variance explained by an affine combination of multiple explanatory covariates. An attribution of this exp…

math.PR201918 cited

On strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables

Julyan Arbel, Olivier Marchal, Hien D. Nguyen

We investigate the sub-Gaussian property for almost surely bounded random variables. If sub-Gaussianity per se is de facto ensured by the bounded support of said random variables,…