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05/19/2023
Must the Communication Graph of MPC Protocols be an Expander?
Secure multiparty computation (MPC) on incomplete communication networks...
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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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10/18/2021
Flexible Accuracy for Differential Privacy
Differential Privacy (DP) has become a gold standard in privacy-preservi...
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07/29/2021
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning
Traditionally, federated learning (FL) aims to train a single global mod...
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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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02/23/2021
QuPeL: Quantized Personalization with Applications to Federated Learning
Traditionally, federated learning (FL) aims to train a single global mod...
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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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06/22/2020
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
We study stochastic gradient descent (SGD) with local iterations in the ...
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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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05/16/2020
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data
We study distributed stochastic gradient descent (SGD) in the master-wor...
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05/13/2020
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization
In this paper, we consider the problem of communication-efficient decent...
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10/31/2019
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization
In this paper, we propose and analyze SPARQ-SGD, which is an event-trigg...
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07/05/2019
Data Encoding for Byzantine-Resilient Distributed Optimization
We study distributed optimization in the presence of Byzantine adversari...
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06/06/2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations
Communication bottleneck has been identified as a significant issue in d...
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12/10/2018
