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A New Linear Scaling Rule for Private Adaptive Hyperparameter
  Optimization
v1v2v3 (latest)

A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization

International Conference on Machine Learning (ICML), 2022
8 December 2022
Ashwinee Panda
Xinyu Tang
Saeed Mahloujifar
Vikash Sehwag
Prateek Mittal
ArXiv (abs)PDFHTMLGithub (1760★)

Papers citing "A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization"

11 / 11 papers shown
On Optimal Hyperparameters for Differentially Private Deep Transfer Learning
On Optimal Hyperparameters for Differentially Private Deep Transfer Learning
Aki Rehn
Linzh Zhao
Mikko Heikkilä
Antti Honkela
168
0
0
23 Oct 2025
An Interactive Framework for Finding the Optimal Trade-off in Differential Privacy
An Interactive Framework for Finding the Optimal Trade-off in Differential Privacy
Yaohong Yang
Aki Rehn
Sammie Katt
Antti Honkela
Samuel Kaski
201
1
0
04 Sep 2025
Spurious Privacy Leakage in Neural Networks
Spurious Privacy Leakage in Neural Networks
Chenxiang Zhang
Jun Pang
S. Mauw
394
1
0
26 May 2025
Privacy Auditing of Large Language Models
Privacy Auditing of Large Language ModelsInternational Conference on Learning Representations (ICLR), 2025
Ashwinee Panda
Xinyu Tang
Milad Nasr
Christopher A. Choquette-Choo
Prateek Mittal
PILM
517
23
0
09 Mar 2025
Towards hyperparameter-free optimization with differential privacy
Towards hyperparameter-free optimization with differential privacyInternational Conference on Learning Representations (ICLR), 2025
Zhiqi Bu
Ruixuan Liu
345
7
0
02 Mar 2025
Privacy Amplification for the Gaussian Mechanism via Bounded Support
Privacy Amplification for the Gaussian Mechanism via Bounded Support
Shengyuan Hu
Saeed Mahloujifar
Virginia Smith
Kamalika Chaudhuri
Chuan Guo
FedML
268
1
0
07 Mar 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization
Private Fine-tuning of Large Language Models with Zeroth-order Optimization
Xinyu Tang
Ashwinee Panda
Milad Nasr
Saeed Mahloujifar
Prateek Mittal
623
43
0
09 Jan 2024
DP-Mix: Mixup-based Data Augmentation for Differentially Private
  Learning
DP-Mix: Mixup-based Data Augmentation for Differentially Private LearningNeural Information Processing Systems (NeurIPS), 2023
Wenxuan Bao
Francesco Pittaluga
Vijay Kumar
Vincent Bindschaedler
292
15
0
02 Nov 2023
Differentially Private Sharpness-Aware Training
Differentially Private Sharpness-Aware TrainingInternational Conference on Machine Learning (ICML), 2023
Jinseong Park
Hoki Kim
Yujin Choi
Jaewook Lee
302
15
0
09 Jun 2023
Selective Pre-training for Private Fine-tuning
Selective Pre-training for Private Fine-tuning
Da Yu
Sivakanth Gopi
Janardhan Kulkarni
Zinan Lin
Saurabh Naik
Tomasz Religa
Jian Yin
Huishuai Zhang
461
26
0
23 May 2023
Privacy-Preserving In-Context Learning for Large Language Models
Privacy-Preserving In-Context Learning for Large Language ModelsInternational Conference on Learning Representations (ICLR), 2023
Tong Wu
Ashwinee Panda
Jiachen T. Wang
Prateek Mittal
430
57
0
02 May 2023
1
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