Privately Customizing Prefinetuning to Better Match User Data in
Federated Learning

Privately Customizing Prefinetuning to Better Match User Data in Federated Learning

17 February 2023

Akshat Shrivastava

Papers citing "Privately Customizing Prefinetuning to Better Match User Data in Federated Learning"

16 / 16 papers shown

Title
AugFL: Augmenting Federated Learning with Pretrained Models Sheng Yue Zerui Qin Yongheng Deng Ju Ren Yaoxue Zhang Junshan Zhang FedML 85 0 0 04 Mar 2025
Ten Challenging Problems in Federated Foundation Models Tao Fan Hanlin Gu Xuemei Cao Chee Seng Chan Qian Chen ... Y. Zhang Xiaojin Zhang Zhenzhe Zheng Lixin Fan Qiang Yang FedML 83 4 0 14 Feb 2025
Distributed, communication-efficient, and differentially private estimation of KL divergence Mary Scott Sayan Biswas Graham Cormode Carsten Maple FedML 75 0 0 25 Nov 2024
Differentially Private Kernel Density Estimation Erzhi Liu Jerry Yao-Chieh Hu Alex Reneau Zhao Song Han Liu 66 3 0 03 Sep 2024
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas Chengyuan Deng Yiqun Duan Xin Jin Heng Chang Yijun Tian ... Kuofeng Gao Sihong He Jun Zhuang Lu Cheng Haohan Wang AILaw 40 16 0 08 Jun 2024
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs Charlie Hou Akshat Shrivastava Hongyuan Zhan Rylan Conway Trang Le Adithya Sagar Giulia Fanti Daniel Lazar 26 8 0 05 Jun 2024
Prompt Public Large Language Models to Synthesize Data for Private On-device Applications Shanshan Wu Zheng Xu Yanxiang Zhang Yuanbo Zhang Daniel Ramage SyDa 21 9 0 05 Apr 2024
Efficiently Computing Similarities to Private Datasets A. Backurs Zinan Lin S. Mahabadi Sandeep Silwal Jakub Tarnawski 65 4 0 13 Mar 2024
On the Convergence of Differentially-Private Fine-tuning: To Linearly Probe or to Fully Fine-tune? Shuqi Ke Charlie Hou Giulia Fanti Sewoong Oh 36 4 0 29 Feb 2024
Grounding Foundation Models through Federated Transfer Learning: A General Framework Yan Kang Tao Fan Hanlin Gu Xiaojin Zhang Lixin Fan Qiang Yang AI4CE 68 19 0 29 Nov 2023
Privacy in Large Language Models: Attacks, Defenses and Future Directions Haoran Li Yulin Chen Jinglong Luo Yan Kang Xiaojin Zhang Qi Hu Chunkit Chan Yangqiu Song PILM 42 41 0 16 Oct 2023
GPT-FL: Generative Pre-trained Model-Assisted Federated Learning Tuo Zhang Tiantian Feng Samiul Alam Dimitrios Dimitriadis Sunwoo Lee Mi Zhang Shrikanth S. Narayanan Salman Avestimehr FedML 13 27 0 03 Jun 2023
Selective Pre-training for Private Fine-tuning Da Yu Sivakanth Gopi Janardhan Kulkarni Zi-Han Lin Saurabh Naik Tomasz Religa Jian Yin Huishuai Zhang 32 19 0 23 May 2023
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 132 119 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 152 349 0 25 Sep 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 290 1,814 0 14 Dec 2020