368 citations · 552 across the 22 of their papers we have counts for
6 papers · 1 filter
Can You Really Backdoor Federated Learning?
Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh +1
The decentralized nature of federated learning makes detecting and defending against adversarial attacks a challenging task. This paper focuses on backdoor attacks in the federated…
Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent +56
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a cen…
Estimating Entropy of Distributions in Constant Space
Jayadev Acharya, Sourbh Bhadane, Piotr Indyk +1
We consider the task of estimating the entropy of -ary distributions from samples in the streaming model, where space is limited. Our main contribution is an algorithm that requ…
Context-Aware Local Differential Privacy
Jayadev Acharya, Keith Bonawitz, Peter Kairouz +2
Local differential privacy (LDP) is a strong notion of privacy for individual users that often comes at the expense of a significant drop in utility. The classical definition of LD…
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…
Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters
Jayadev Acharya, Ziteng Sun
We consider the problems of distribution estimation and heavy hitter (frequency) estimation under privacy and communication constraints. While these constraints have been studied s…