P. Kairouz

发表

Advances and Open Problems in Federated Learning pdf

Richard Nock, Zaïd Harchaoui, David Evans, 2019, Found. Trends Mach. Learn..

Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Federated Learning pdf

Peter Kairouz, Amir Houmansadr, Daniel Ramage, 2021, ArXiv.

Generative Models for Effective ML on Private, Decentralized Datasets pdf

H. Brendan McMahan, Peter Kairouz, Swaroop Ramaswamy, 2019, ICLR.

The Composition Theorem for Differential Privacy

Pramod Viswanath, Sewoong Oh, Peter Kairouz, 2013, IEEE Transactions on Information Theory.

Discrete Distribution Estimation under Local Privacy pdf

Peter Kairouz, Daniel Ramage, Keith Bonawitz, 2016, ICML.

The Staircase Mechanism in Differential Privacy

Pramod Viswanath, Sewoong Oh, Peter Kairouz, 2015, IEEE Journal of Selected Topics in Signal Processing.

On the Rényi Differential Privacy of the Shuffle Model

Antonious M. Girgis, A. Suresh, P. Kairouz, 2021, CCS.

Shuffled Model of Differential Privacy in Federated Learning

Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz, 2021, AISTATS.

Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints pdf

Ayfer Özgür, Peter Kairouz, Wei-Ning Chen, 2021, COLT.

(Nearly) Dimension Independent Private ERM with AdaGrad Ratesvia Publicly Estimated Subspaces

Peter Kairouz, Abhradeep Thakurta, Keith Rush, 2021, COLT.

The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation pdf

Thomas Steinke, Peter Kairouz, Ziyu Liu, 2021, ICML.

PRIVATE, DECENTRALIZED DATASETS

H. B. McMahan, D. Ramage, P. Kairouz, 2020 .

Lower Bounds for the Minimum Mean-Square Error via Neural Network-based Estimation pdf

Peter Kairouz, Lalitha Sankar, Mario Diaz, 2021, ArXiv.

Privacy-first health research with federated learning

M. Marathe, M. Howell, P. Eastham, 2020, npj Digital Medicine.

Context-Aware Generative Adversarial Privacy

Ram Rajagopal, Xiao Chen, Peter Kairouz, 2017, Entropy.

Optimal Compression of Locally Differentially Private Mechanisms pdf

Lucas Theis, Peter Kairouz, Abhin Shah, 2021, ArXiv.

DP-CGAN: Differentially Private Synthetic Data and Label Generation

Reihaneh Torkzadehmahani, Benedict Paten, Peter Kairouz, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

MIMO communications over multi-mode optical fibers

Peter Kairouz, P. Kairouz, 2013 .

Context-Aware Local Differential Privacy pdf

Peter Kairouz, Daniel Ramage, Keith Bonawitz, 2019, ICML.

Censored and Fair Universal Representations using Generative Adversarial Models

Peter Kairouz, Jiachun Liao, Chong Huang, 2019 .

On the Optimality of the Kautz-Singleton Construction in Probabilistic Group Testing

Ayfer Özgür, Peter Kairouz, Mary Wootters, 2019, IEEE Transactions on Information Theory.

C 2012 Peter Kairouz Mimo Communications over Multi-mode Optical Fibers

P. Kairouz, 2022 .

A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization

John Kevin Cava, P. Kairouz, Mario Díaz, 2022, IEEE Transactions on Information Theory.

Series Editorial: The Second Issue of the Series on Machine Learning in Communications and Networks

Walid Saad, Deniz Gündüz, Zhijin Qin, 2021, IEEE J. Sel. Areas Commun..

Censored and Fair Universal Representations using Generative Adversarial Models

P. Kairouz, Jiachun Liao, L. Sankar, 2019 .

Series Editorial The Fourth Issue of the Series on Machine Learning in Communications and Networks

Walid Saad, Deniz Gündüz, Ayfer Özgür, 2022, IEEE J. Sel. Areas Commun..

Series Editorial: Inauguration Issue of the Series on Machine Learning in Communications and Networks

Jaafar M. H. Elmirghani, Geoffrey Ye Li, Zhijin Qin, 2021, IEEE J. Sel. Areas Commun..

Series Editorial: The Third Issue of the Series on Machine Learning in Communications and Networks

Walid Saad, Jaafar M. H. Elmirghani, Deniz Gündüz, 2021, IEEE J. Sel. Areas Commun..

Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation

Kallista A. Bonawitz, P. Kairouz, M. Gruteser, 2021, Proc. Priv. Enhancing Technol..

Lower Bounds for the MMSE via Neural Network Estimation and Their Applications to Privacy

P. Kairouz, Mario Díaz, L. Sankar, 2021, 2108.12851.

The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation

P. Kairouz, T. Steinke, Ziyu Liu, 2021, ICML.

Histogram Estimation under User-level Privacy with Heterogeneous Data

A. Suresh, Yuhan Liu, P. Kairouz, 2022, ArXiv.

Generative Models for Effective ML on Private, Decentralized Datasets

H. B. McMahan, D. Ramage, B. A. Y. Arcas, 2019, ICLR.

A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization

John Kevin Cava, P. Kairouz, Mario Díaz, 2019, IEEE Transactions on Information Theory.

The Poisson binomial mechanism for secure and private federated learning

P. Kairouz, Ayfer Özgür, Wei-Ning Chen, 2022, ArXiv.

Theoretical Guarantees for Model Auditing with Finite Adversaries pdf

Peter Kairouz, Lalitha Sankar, Jiachun Liao, 2019, ArXiv.

Can You Really Backdoor Federated Learning? pdf

Ananda Theertha Suresh, H. Brendan McMahan, Peter Kairouz, 2019, ArXiv.

Federated Heavy Hitters Discovery with Differential Privacy

H. Brendan McMahan, Peter Kairouz, Wei Li, 2019, AISTATS.

A Field Guide to Federated Optimization pdf

Suhas Diggavi, Ameet Talwalkar, Tara Javidi, 2021, ArXiv.

Challenges towards the Next Frontier in Privacy

Ryan M. Rogers, Weijie J. Su, Nicolas Papernot, 2023, ArXiv.

Differentially Private Stream Processing at Scale

Abhradeep Thakurta, P. Kairouz, T. Steinke, 2023, ArXiv.

Practical and Private (Deep) Learning without Sampling or Shuffling pdf

Peter Kairouz, Shuang Song, Abhradeep Thakurta, 2021, ICML.

Generating Fair Universal Representations Using Adversarial Models

Maunil R. Vyas, P. Kairouz, Jiachun Liao, 2019, IEEE Transactions on Information Forensics and Security.

Extremal Mechanisms for Local Differential Privacy

Pramod Viswanath, Sewoong Oh, Peter Kairouz, 2014, J. Mach. Learn. Res..

Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning

Peter Kairouz, Amir Houmansadr, Daniel Ramage, 2021, 2022 IEEE Symposium on Security and Privacy (SP).

Privacy Amplification via Random Check-Ins pdf

Borja Balle, H. Brendan McMahan, Peter Kairouz, 2020, NeurIPS.

The Skellam Mechanism for Differentially Private Federated Learning pdf

Peter Kairouz, Naman Agarwal, Ziyu Liu, 2021, NeurIPS.

Hiding the Rumor Source

Kannan Ramchandran, Pramod Viswanath, Sewoong Oh, 2015, IEEE Transactions on Information Theory.

Metadata-Conscious Anonymous Messaging

Kannan Ramchandran, Pramod Viswanath, Sewoong Oh, 2016, IEEE Transactions on Signal and Information Processing over Networks.

Federated Learning and Privacy

H. Brendan McMahan, Peter Kairouz, Daniel Ramage, 2021, ACM Queue.

The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation

P. Kairouz, Ayfer Özgür, Wei-Ning Chen, 2022, ICML.

Unleashing the Power of Randomization in Auditing Differentially Private ML

Sewoong Oh, H. B. McMahan, P. Kairouz, 2023, NeurIPS.

One-shot Empirical Privacy Estimation for Federated Learning

Sewoong Oh, H. B. McMahan, V. Suriyakumar, 2023, ArXiv.

Federated Learning of Gboard Language Models with Differential Privacy

Christopher A. Choquette-Choo, H. B. McMahan, P. Kairouz, 2023, ArXiv.

Sparse Combinatorial Group Testing

Ayfer Özgür, Peter Kairouz, Huseyin A. Inan, 2017, IEEE Transactions on Information Theory.

Sparse group testing codes for low-energy massive random access

Ayfer Özgür, Peter Kairouz, Huseyin A. Inan, 2017, 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

A Tunable Loss Function for Binary Classification

Peter Kairouz, Lalitha Sankar, Mario Diaz, 2019, 2019 IEEE International Symposium on Information Theory (ISIT).

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

Suhas Diggavi, Ananda Theertha Suresh, Peter Kairouz, 2021, IEEE Journal on Selected Areas in Information Theory.

Generative Adversarial Privacy: A Data-Driven Approach to Information-Theoretic Privacy pdf

Ram Rajagopal, Xiao Chen, Peter Kairouz, 2018, 2018 52nd Asilomar Conference on Signals, Systems, and Computers.

Algorithms for bounding contribution for histogram estimation under user-level privacy

A. Suresh, Yuhan Liu, P. Kairouz, 2022, ICML.

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

Ananda Theertha Suresh, Peter Kairouz, Suhas Diggavi, 2020, ArXiv.

The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning

Christopher A. Choquette-Choo, A. Suresh, P. Kairouz, 2022, ICML.

A Tunable Loss Function for Classification pdf

Peter Kairouz, Lalitha Sankar, Gautam Dasarathy, 2019, ArXiv.

A Class of Parameterized Loss Functions for Classification: Optimization Tradeoffs and Robustness Characteristics.

P. Kairouz, Mario Díaz, L. Sankar, 2019 .

Dimension Independence in Unconstrained Private ERM via Adaptive Preconditioning pdf

Peter Kairouz, Abhradeep Thakurta, M'onica Ribero, 2020, ArXiv.

Federated Heavy Hitters with Differential Privacy.

Wei Li, Peter Kairouz, Wennan Zhu, 2019 .

Breaking the Communication-Privacy-Accuracy Trilemma pdf

Ayfer Özgür, Wei-Ning Chen, Peter Kairouz, 2020, IEEE Transactions on Information Theory.

Learning Generative Adversarial RePresentations (GAP) under Fairness and Censoring Constraints pdf

Peter Kairouz, Chong Huang, Lalitha Sankar, 2019, ArXiv.

Federated Learning of Gboard Language Models with Differential Privacy

Christopher A. Choquette-Choo, H. B. McMahan, P. Kairouz, 2023, ACL.

Federated Heavy Hitter Recovery under Linear Sketching

A. Suresh, P. Kairouz, Adrià Gascón, 2023, ICML.

Private Federated Frequency Estimation: Adapting to the Hardness of the Instance

P. Kairouz, V. Braverman, Wennan Zhu, 2023, arXiv.org.

A Group Testing Approach to Random Access for Short-Packet Communication

Ayfer Özgür, Peter Kairouz, Surin Ahn, 2019, 2019 IEEE International Symposium on Information Theory (ISIT).

Energy-limited Massive Random Access via Noisy Group Testing

Ayfer Özgür, Peter Kairouz, Huseyin A. Inan, 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

Spy vs. Spy

Pramod Viswanath, Sewoong Oh, Peter Kairouz, 2014, SIGMETRICS.

Privacy-Utility Trades in Crowdsourced Signal Map Obfuscation pdf

Konstantinos Psounis, Matthew A. Clark, Peter Kairouz, 2022, Comput. Networks.

Siamese Generative Adversarial Privatizer for Biometric Data pdf

Tomasz Trzcinski, Ram Rajagopal, Peter Kairouz, 2018, ACCV.

Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation

P. Kairouz, Ayfer Özgür, Wei-Ning Chen, 2023, ArXiv.

Optimal Compression of Locally Differentially Private Mechanisms

Lucas Theis, P. Kairouz, J. Ballé, 2021, AISTATS.

Pointwise Bounds for Distribution Estimation under Communication Constraints pdf

Ayfer Özgür, Peter Kairouz, Wei-Ning Chen, 2021, NeurIPS.

Context-Aware Local Differential Privacy

Kallista A. Bonawitz, P. Kairouz, Ziteng Sun, 2019, ICML.

Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints

Peter Kairouz, Jayadev Acharya, Ziteng Sun, 2021, ALT.

Fair Universal Representations using Adversarial Models

P. Kairouz, Jiachun Liao, L. Sankar, 2022 .

On the Optimality of the Kautz-Singleton Construction in Probabilistic Group Testing

Ayfer Özgür, Peter Kairouz, Mary Wootters, 2018, 2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Neural Network-based Estimation of the MMSE

Peter Kairouz, Lalitha Sankar, Mario Díaz, 2021, 2021 IEEE International Symposium on Information Theory (ISIT).

Differentially private multi-party computation

Pramod Viswanath, Sewoong Oh, Peter Kairouz, 2016, 2016 Annual Conference on Information Science and Systems (CISS).

Secure Multi-party Differential Privacy

Pramod Viswanath, Sewoong Oh, Peter Kairouz, 2015, NIPS.

Differentially Private Multi-party Computation: Optimality of Non-Interactive Randomized Response

Pramod Viswanath, Sewoong Oh, Peter Kairouz, 2014, 1407.1546.

User Inference Attacks on Large Language Models

Christopher A. Choquette-Choo, P. Kairouz, Nikhil Kandpal, 2023, ArXiv.

One-shot Empirical Privacy Estimation for Federated Learning

Sewoong Oh, H. B. McMahan, V. Suriyakumar, 2023, ArXiv.

Private Federated Learning with Autotuned Compression

Christopher A. Choquette-Choo, Sewoong Oh, P. Kairouz, 2023, ICML.

On the Optimality of the Kautz-Singleton Construction in Probabilistic Group Testing

Huseyin A. Inan, P. Kairouz, Mary Wootters, 2018, 2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Sparse Combinatorial Group Testing for Low-Energy Massive Random Access pdf

Ayfer Özgür, Peter Kairouz, Huseyin A. Inan, 2017, ArXiv.

Privacy-Preserving Instructions for Aligning Large Language Models

P. Kairouz, Zheng Xu, Da Yu, 2024, ICML.

Breaking the Communication-Privacy-Accuracy Trilemma pdf

Ayfer Özgür, Peter Kairouz, Wei-Ning Chen, 2020, IEEE Transactions on Information Theory.

MIMO Communications over Multi-Mode Optical Fibers: Capacity Analysis and Input-Output Coupling Schemes pdf

Andrew C. Singer, Peter Kairouz, A. Singer, 2013, ArXiv.

Federated learning and privacy

Kallista A. Bonawitz, H. B. McMahan, P. Kairouz, 2022, ACM Queue.

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

Antonious M. Girgis, A. Suresh, P. Kairouz, 2020, ArXiv.

Communication Efﬁcient Federated Learning with Secure Aggregation and Differential Privacy

Christopher A. Choquette-Choo, Phillip B. Gibbons, Ameet S. Talwalkar, 2021 .