← Authors

Peter Kairouz

35 papers · 2014–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (7) 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (11) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (30) 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ† Keyword Champion πŸ”¬ Deep Specialist (26) πŸ’Ž Century Club (35) πŸ“ˆ Trend Setter ❓ The Questioner ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (98) πŸ”₯ Unstoppable (6)

Conferences

ICML (14) NIPS (9) AISTATS (3) ACL (2) COLT (2) ICLR (2) ALT (1) EMNLP (1) JMLR (1)

Top co-authors

Sewoong Oh (10) Wei-Ning Chen (8) Zheng Xu (5) Pramod Viswanath (5) Ayfer Ozgur (5) Ananda Theertha Suresh (4) Brendan Mcmahan (4) Galen Andrew (3) Alina Oprea (3) Wennan Zhu (3)

Research topics

Differential Privacy (4) Privacy (2)

Keywords

differential privacy (21) federated learning (13) secure aggregation (6) stochastic gradient descent (4) communication efficiency (4) local differential privacy (4) communication constraint (3) randomized response (3) distribution estimation (3) large language model (2) staircase mechanism (2) distributed mean estimation (2) frequency estimation (2) privacy mechanism (2) privacy amplification (2) local privacy (2) distributed learning (2) communication compression (2) stochastic optimization (2) network analysis (1)

Papers

Language Models May Verbatim Complete Text They Were Not Explicitly Trained On ICML 2025
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy ICML 2024
Privacy-Preserving Instructions for Aligning Large Language Models ICML 2024
One-shot Empirical Privacy Estimation for Federated Learning ICLR 2024
Can LLMs get help from other LLMs without revealing private information? ACL 2024
User Inference Attacks on Large Language Models EMNLP 2024
Algorithms for bounding contribution for histogram estimation under user-level privacy ICML 2023
Private Federated Learning with Autotuned Compression ICML 2023
Private Federated Frequency Estimation: Adapting to the Hardness of the Instance NIPS 2023
Unleashing the Power of Randomization in Auditing Differentially Private ML NIPS 2023
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation NIPS 2023
Federated Learning of Gboard Language Models with Differential Privacy ACL 2023
Federated Heavy Hitter Recovery under Linear Sketching ICML 2023
Optimal Compression of Locally Differentially Private Mechanisms AISTATS 2022
The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation ICML 2022
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning ICML 2022
(Nearly) Dimension Independent Private ERM with AdaGrad Rates\{via Publicly Estimated Subspaces COLT 2021
Pointwise Bounds for Distribution Estimation under Communication Constraints NIPS 2021
The Skellam Mechanism for Differentially Private Federated Learning NIPS 2021
Shuffled Model of Differential Privacy in Federated Learning AISTATS 2021
Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints ALT 2021
Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints COLT 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation ICML 2021
Practical and Private (Deep) Learning Without Sampling or Shuffling ICML 2021
Generative Models for Effective ML on Private, Decentralized Datasets ICLR 2020
Federated Heavy Hitters Discovery with Differential Privacy AISTATS 2020
Privacy Amplification via Random Check-Ins NIPS 2020
Breaking the Communication-Privacy-Accuracy Trilemma NIPS 2020
Context Aware Local Differential Privacy ICML 2020
Extremal Mechanisms for Local Differential Privacy JMLR 2016
Metadata-conscious anonymous messaging ICML 2016
Discrete Distribution Estimation under Local Privacy ICML 2016
The Composition Theorem for Differential Privacy ICML 2015
Secure Multi-party Differential Privacy NIPS 2015
Extremal Mechanisms for Local Differential Privacy NIPS 2014