A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs

A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs

16 August 2024

Zheng Xu

Papers citing "A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs"

8 / 8 papers shown

Title
An Inversion Theorem for Buffered Linear Toeplitz (BLT) Matrices and Applications to Streaming Differential Privacy H. B. McMahan Krishna Pillutla 31 0 0 30 Apr 2025
Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning Marshall Ball James Bell-Clark Adria Gascon Peter Kairouz Sewoong Oh Zhiye Xie FedML 21 0 0 15 Oct 2024
Federated Learning in Practice: Reflections and Projections Katharine Daly Hubert Eichner Peter Kairouz H. B. McMahan Daniel Ramage Zheng Xu FedML 53 5 0 11 Oct 2024
Near Exact Privacy Amplification for Matrix Mechanisms Christopher A. Choquette-Choo Arun Ganesh Saminul Haque Thomas Steinke Abhradeep Thakurta 36 5 0 08 Oct 2024
Fine-Tuning Large Language Models with User-Level Differential Privacy Zachary Charles Arun Ganesh Ryan McKenna H. B. McMahan Nicole Mitchell Krishna Pillutla Keith Rush 19 11 0 10 Jul 2024
Banded Square Root Matrix Factorization for Differentially Private Model Training Nikita Kalinin Christoph H. Lampert 26 5 0 22 May 2024
Papaya: Practical, Private, and Scalable Federated Learning Dzmitry Huba John Nguyen Kshitiz Malik Ruiyu Zhu Michael G. Rabbat ... H. Srinivas Kaikai Wang Anthony Shoumikhin Jesik Min Mani Malek FedML 99 135 0 08 Nov 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 173 410 0 14 Jul 2021