11 citations · 24 across the 11 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
math.ST2023
Differentially Private Permutation Tests
Ilmun Kim, Antonin Schrab
Recent years have witnessed growing concerns about the privacy of sensitive data. In response to these concerns, differential privacy has emerged as a rigorous framework for privac…
stat.ML2023★ 5 cited
MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting
Felix Biggs, Antonin Schrab, Arthur Gretton
We propose novel statistics which maximise the power of a two-sample test based on the Maximum Mean Discrepancy (MMD), by adapting over the set of kernels used in defining it. For…