Peter Kairouz
Orcid: 0000-0001-6897-5937
According to our database1,
Peter Kairouz
authored at least 104 papers
between 2012 and 2024.
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Bibliography
2024
Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning.
IACR Cryptol. ePrint Arch., 2024
CoRR, 2024
Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition.
CoRR, 2024
Improved Communication-Privacy Trade-offs in L<sub>2</sub> Mean Estimation under Streaming Differential Privacy.
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Improved Communication-Privacy Trade-offs in L2 Mean Estimation under Streaming Differential Privacy.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
2023
IEEE Trans. Inf. Theory, February, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Algorithms for bounding contribution for histogram estimation under user-level privacy.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023
2022
A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization.
IEEE Trans. Inf. Theory, 2022
IEEE Trans. Inf. Forensics Secur., 2022
Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation.
Proc. Priv. Enhancing Technol., 2022
Series Editorial The Sixth Issue of the Series on Machine Learning in Communications and Networks.
IEEE J. Sel. Areas Commun., 2022
Series Editorial The Fourth Issue of the Series on Machine Learning in Communications and Networks.
IEEE J. Sel. Areas Commun., 2022
IEEE J. Sel. Areas Commun., 2022
Comput. Networks, 2022
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning.
Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022
The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation.
Proceedings of the International Conference on Machine Learning, 2022
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Federated Learning and Privacy: Building privacy-preserving systems for machine learning and data science on decentralized data.
ACM Queue, 2021
Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs.
IEEE J. Sel. Areas Inf. Theory, 2021
Series Editorial: The Third Issue of the Series on Machine Learning in Communications and Networks.
IEEE J. Sel. Areas Commun., 2021
Series Editorial: The Second Issue of the Series on Machine Learning in Communications and Networks.
IEEE J. Sel. Areas Commun., 2021
Series Editorial: Inauguration Issue of the Series on Machine Learning in Communications and Networks.
IEEE J. Sel. Areas Commun., 2021
CoRR, 2021
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Federated Learning.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the IEEE International Symposium on Information Theory, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation.
Proceedings of the 38th International Conference on Machine Learning, 2021
(Nearly) Dimension Independent Private ERM with AdaGrad Ratesvia Publicly Estimated Subspaces.
Proceedings of the Conference on Learning Theory, 2021
Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints.
Proceedings of the Conference on Learning Theory, 2021
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021
Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints.
Proceedings of the Algorithmic Learning Theory, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs.
CoRR, 2020
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
On the Optimality of the Kautz-Singleton Construction in Probabilistic Group Testing.
IEEE Trans. Inf. Theory, 2019
Learning Generative Adversarial RePresentations (GAP) under Fairness and Censoring Constraints.
CoRR, 2019
Proceedings of the IEEE International Symposium on Information Theory, 2019
Proceedings of the IEEE International Symposium on Information Theory, 2019
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019
2018
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
Generative Adversarial Privacy: A Data-Driven Approach to Information-Theoretic Privacy.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018
Proceedings of the Computer Vision - ACCV 2018, 2018
2017
Asynchronous and noncoherent neighbor discovery for the IoT using sparse-graph codes.
Proceedings of the IEEE International Conference on Communications, 2017
Proceedings of the 55th Annual Allerton Conference on Communication, 2017
2016
IEEE Trans. Signal Inf. Process. over Networks, 2016
Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science, 2016
Proceedings of the 33nd International Conference on Machine Learning, 2016
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016
2015
IEEE J. Sel. Top. Signal Process., 2015
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
2014
2013
MIMO Communications over Multi-Mode Optical Fibers: Capacity Analysis and Input-Output Coupling Schemes
CoRR, 2013
Proceedings of the IEEE International Conference on Acoustics, 2013
2012
Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012
Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012