DPMLBench: Holistic Evaluation of Differentially Private Machine
Learning

DPMLBench: Holistic Evaluation of Differentially Private Machine Learning

10 May 2023

Papers citing "DPMLBench: Holistic Evaluation of Differentially Private Machine Learning"

9 / 9 papers shown

Title
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis Chen Gong Kecen Li Zinan Lin Tianhao Wang 47 3 0 18 Mar 2025
PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Model Haiming Wang Zhikun Zhang Tianhao Wang Shibo He Michael Backes Jiming Chen Yang Zhang 25 35 0 02 Oct 2022
AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy L. Du Zhikun Zhang Shaojie Bai Changchang Liu S. Ji Peng Cheng Jiming Chen 88 36 0 14 Oct 2021
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 344 0 13 Oct 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 123 119 0 07 Oct 2021
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 144 347 0 25 Sep 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu Huishuai Zhang Wei Chen Tie-Yan Liu FedML SILM 91 110 0 25 Feb 2021
Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 128 178 0 28 Jul 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 185 357 0 24 Mar 2020