Deepesh Data

IEEE Trans. Inf. Theory, October, 2023

Must the Communication Graph of MPC Protocols be an Expander?

[BibT_eX]

[DOI]

J. Cryptol., July, 2023

SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Optimization.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., February, 2023

A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

A Generative Framework for Personalized Learning and Estimation: Theory, Algorithms, and Privacy.

[BibT_eX]

[DOI]

CoRR, 2022

Distributed User-Level Private Mean Estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2022

Decentralized Learning Robust to Data Poisoning Attacks.

[BibT_eX]

[DOI]

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Flexible Accuracy for Differential Privacy.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Data Encoding for Byzantine-Resilient Distributed Optimization.

[BibT_eX]

[DOI]

Linqi Song

IEEE Trans. Inf. Theory, 2021

SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Inf. Theory, 2021

Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Inf. Theory, 2021

A Field Guide to Federated Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

QuPeL: Quantized Personalization with Applications to Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2021

QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentially Private Federated Learning with Shuffling and Client Self-Sampling.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2021

Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2021

Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

On the Rényi Differential Privacy of the Shuffle Model.

[BibT_eX]

[DOI]

Peter Kairouz

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Shuffled Model of Differential Privacy in Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Interactive Secure Function Computation.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2020

Successive Refinement of Privacy.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Inf. Theory, 2020

Qsparse-Local-SGD: Distributed SGD With Quantization, Sparsification, and Local Computations.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Inf. Theory, 2020

Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs.

[BibT_eX]

[DOI]

CoRR, 2020

Hiding Identities: Estimation Under Local Differential Privacy.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2020

On Byzantine-Resilient High-Dimensional Stochastic Gradient Descent.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization.

[BibT_eX]

[DOI]

CoRR, 2019

Data Encoding Methods for Byzantine-Resilient Distributed Optimization.

[BibT_eX]

[DOI]

Linqi Song

Proceedings of the IEEE International Symposium on Information Theory, 2019

Byzantine-Tolerant Distributed Coordinate Descent.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2019

2018

Data Encoding for Byzantine-Resilient Distributed Gradient Descent.

[BibT_eX]

[DOI]

Linqi Song

Proceedings of the 56th Annual Allerton Conference on Communication, 2018

2017

Towards Characterizing Securely Computable Two-Party Randomized Functions.

[BibT_eX]

[DOI]

Manoj Prabhakaran

IACR Cryptol. ePrint Arch., 2017

Secure computation of randomized functions: Further results.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Information Theory Workshop, 2017

2016

Communication and Randomness Lower Bounds for Secure Computation.

[BibT_eX]

[DOI]

Manoj M. Prabhakaran

IEEE Trans. Inf. Theory, 2016

Secure computation of randomized functions.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2016

2015

On the Communication Complexity of Secure Computation.

[BibT_eX]

[DOI]

Manoj Prabhakaran

IACR Cryptol. ePrint Arch., 2015

On coding for secure computing.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2015

2014

How to securely compute the modulo-two sum of binary sources.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Information Theory Workshop, 2014

2013

Communication requirements for secure computation.

[BibT_eX]

[DOI]