11 citations · 18 across the 4 of their papers we have counts for
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stat.ML2022★ 7 cited
Efficient Aggregated Kernel Tests using Incomplete -statistics
Antonin Schrab, Ilmun Kim, Benjamin Guedj +1
We propose a series of computationally efficient nonparametric tests for the two-sample, independence, and goodness-of-fit problems, using the Maximum Mean Discrepancy (MMD), Hilbe…
cs.CL2022
Reprint: a randomized extrapolation based on principal components for data augmentation
Le Li, Jiale Wei, Pai Peng +3
Data scarcity and data imbalance have attracted a lot of attention in many fields. Data augmentation, explored as an effective approach to tackle them, can improve the robustness a…
stat.ML2022
KSD Aggregated Goodness-of-fit Test
Antonin Schrab, Benjamin Guedj, Arthur Gretton
We investigate properties of goodness-of-fit tests based on the Kernel Stein Discrepancy (KSD). We introduce a strategy to construct a test, called KSDAgg, which aggregates multipl…