36 citations · 176 across the 38 of their papers we have counts for
6 papers · 1 filter
Uniformity Testing in the Shuffle Model: Simpler, Better, Faster
Clément L. Canonne, Hongyi Lyu
Uniformity testing, or testing whether independent observations are uniformly distributed, is the prototypical question in distribution testing. Over the past years, a line of work…
Optimal Rates for Nonparametric Density Estimation under Communication Constraints
Jayadev Acharya, Clément L. Canonne, Aditya Vikram Singh +1
We consider density estimation for Besov spaces when each sample is quantized to only a limited number of bits. We provide a noninteractive adaptive estimator that exploits the spa…
The Price of Tolerance in Distribution Testing
Clément L. Canonne, Ayush Jain, Gautam Kamath +1
We revisit the problem of tolerant distribution testing. That is, given samples from an unknown distribution over , is it -close to or $\varepsi…
Identity testing under label mismatch
Clément L. Canonne, Karl Wimmer
Testing whether the observed data conforms to a purported model (probability distribution) is a basic and fundamental statistical task, and one that is by now well understood. Howe…
Information-constrained optimization: can adaptive processing of gradients help?
Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar +1
We revisit first-order optimization under local information constraints such as local privacy, gradient quantization, and computational constraints limiting access to a few coordin…
Inference under Information Constraints III: Local Privacy Constraints
Jayadev Acharya, Clément L. Canonne, Cody Freitag +2
We study goodness-of-fit and independence testing of discrete distributions in a setting where samples are distributed across multiple users. The users wish to preserve the privacy…