Communication-Constrained Hypothesis Testing: Optimality, Robustness, and Reverse Data Processing Inequalities
Communication-Constrained Hypothesis Testing: Optimality, Robustness, and Reverse Data Processing Inequalities
We study hypothesis testing under communication constraints, where each sample is quantized before being revealed to a statistician. Without communication constraints, it is well known that the sample complexity of simple binary hypothesis testing is characterized by the Hellinger distance between the distributions. We show that the sample complexity of …