activity
20172022
most citedCan You Really Backdoor Federated Learning?

368 citations · 427 across the 10 of their papers we have counts for

collaborators

14 papers

cs.LG20221 cited

Discrete Distribution Estimation under User-level Local Differential Privacy

Jayadev Acharya, Yuhan Liu, Ziteng Sun

We study discrete distribution estimation under user-level local differential privacy (LDP). In user-level -LDP, each user has samples and the privacy of all $…

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.IT20214 cited

Robust Testing and Estimation under Manipulation Attacks

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

We study robust testing and estimation of discrete distributions in the strong contamination model. We consider both the "centralized setting" and the "distributed setting with inf…

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.IT2020

Estimating Sparse Discrete Distributions Under Local Privacy and Communication Constraints

Jayadev Acharya, Peter Kairouz, Yuhan Liu +1

We consider the problem of estimating sparse discrete distributions under local differential privacy (LDP) and communication constraints. We characterize the sample complexity for…

cs.LG2020

Differentially Private Assouad, Fano, and Le Cam

Jayadev Acharya, Ziteng Sun, Huanyu Zhang

Le Cam's method, Fano's inequality, and Assouad's lemma are three widely used techniques to prove lower bounds for statistical estimation tasks. We propose their analogues under ce…