activity
20172026
most citedCan You Really Backdoor Federated Learning?

368 citations · 427 across the 12 of their papers we have counts for

collaborators
Showing cs.DSShow all

5 papers · 1 filter

cs.DS2023

Federated Heavy Hitter Recovery under Linear Sketching

Adria Gascon, Peter Kairouz, Ziteng Sun +1

Motivated by real-life deployments of multi-round federated analytics with secure aggregation, we investigate the fundamental communication-accuracy tradeoffs of the heavy hitter d…

cs.DS20223 cited

The Role of Interactivity in Structured Estimation

Jayadev Acharya, Clément L. Canonne, Ziteng Sun +1

We study high-dimensional sparse estimation under three natural constraints: communication constraints, local privacy constraints, and linear measurements (compressive sensing). Wi…

cs.DS2021

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…

cs.DS20192 cited

Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit

Jayadev Acharya, Clément L. Canonne, Yanjun Han +2

We study goodness-of-fit of discrete distributions in the distributed setting, where samples are divided between multiple users who can only release a limited amount of information…

cs.DS2018

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…