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20062022
most citedHadamard Response: Estimating Distributions Privately, Efficiently, and with Little Communication

97 citations · 543 across the 40 of their papers we have counts for

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Showing 2018 · cs.DSShow all

5 papers · 2 filters

cs.DS2018★ 5 cited

Inference under Information Constraints I: Lower Bounds from Chi-Square Contraction

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

Multiple players are each given one independent sample, about which they can only provide limited information to a central referee. Each player is allowed to describe its observed…

cs.DS2018★ 34 cited

Test without Trust: Optimal Locally Private Distribution Testing

Jayadev Acharya, Clément L. Canonne, Cody Freitag +1

We study the problem of distribution testing when the samples can only be accessed using a locally differentially private mechanism and focus on two representative testing question…

cs.DS2018★ 22 cited

Learning and Testing Causal Models with Interventions

Jayadev Acharya, Arnab Bhattacharyya, Constantinos Daskalakis +1

We consider testing and learning problems on causal Bayesian networks as defined by Pearl (Pearl, 2009). Given a causal Bayesian network on a graph with discrete…

cs.DS2018★ 13 cited

Distributed Simulation and Distributed Inference

Jayadev Acharya, Clément L. Canonne, Himanshu Tyagi

Independent samples from an unknown probability distribution on a domain of size are distributed across players, with each player holding one sample. Each player ca…

cs.DS2018★ 5 cited

INSPECTRE: Privately Estimating the Unseen

Jayadev Acharya, Gautam Kamath, Ziteng Sun +1

We develop differentially private methods for estimating various distributional properties. Given a sample from a discrete distribution , some functional , and accuracy and p…