Sharp Bounds for Generalized Uniformity Testing

Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart

Neural Information Processing Systems 

We establish tight bounds on the sample complexity of generalized uniformity testing. In more detail, we present a computationally efficient tester whose sample complexity is optimal, within constant factors, and a matching worst-case information-theoretic lower bound. Specifically, we show that the sample complexity of generalized uniformitytestingisΘ 1/( 4/3kpk3)+1/( 2kpk2) .