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02/22/2023
Multi-Message Shuffled Privacy in Federated Learning
We study differentially private distributed optimization under communica...
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07/07/2022
Differentially Private Stochastic Linear Bandits: (Almost) for Free
In this paper, we propose differentially private algorithms for the prob...
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07/05/2022
A Generative Framework for Personalized Learning and Estimation: Theory, Algorithms, and Privacy
A distinguishing characteristic of federated learning is that the (local...
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07/19/2021
Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning
We study privacy in a distributed learning framework, where clients coll...
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05/11/2021
On the Renyi Differential Privacy of the Shuffle Model
The central question studied in this paper is Renyi Differential Privacy...
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08/17/2020
Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs
We consider a distributed empirical risk minimization (ERM) optimization...
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05/24/2020
Successive Refinement of Privacy
This work examines a novel question: how much randomness is needed to ac...
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12/06/2018
A Converse Bound for Cache-Aided Interference Networks
In this paper, an interference network with arbitrary number of transmit...
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12/16/2017