Unlocking High-Accuracy Differentially Private Image Classification through Scale

28 April 2022

Papers citing "Unlocking High-Accuracy Differentially Private Image Classification through Scale"

50 / 54 papers shown

Title
Differentially Private 2D Human Pose Estimation Kaushik Bhargav Sivangi Idris Zakariyya Paul Henderson F. Deligianni 76 0 0 14 Apr 2025
DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation Chengkun Wei Weixian Li Chen Gong Wenzhi Chen 48 0 0 29 Mar 2025
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis Chen Gong Kecen Li Zinan Lin Tianhao Wang 47 3 0 18 Mar 2025
Balls-and-Bins Sampling for DP-SGD Lynn Chua Badih Ghazi Charlie Harrison Ethan Leeman Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 80 3 0 21 Dec 2024
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios Sangyeon Yoon Wonje Jeung Albert No 85 0 0 02 Dec 2024
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD Thomas Steinke Milad Nasr Arun Ganesh Borja Balle Christopher A. Choquette-Choo Matthew Jagielski Jamie Hayes Abhradeep Thakurta Adam Smith Andreas Terzis 23 7 0 08 Oct 2024
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction Xinwei Zhang Zhiqi Bu Borja Balle Mingyi Hong Meisam Razaviyayn Vahab Mirrokni 74 2 0 04 Oct 2024
Differentially Private Parameter-Efficient Fine-tuning for Large ASR Models Hongbin Liu Lun Wang Om Thakkar Abhradeep Thakurta Arun Narayanan 23 0 0 02 Oct 2024
Differentially Private Active Learning: Balancing Effective Data Selection and Privacy Kristian Schwethelm Johannes Kaiser Jonas Kuntzer Mehmet Yigitsoy Daniel Rueckert Georgios Kaissis 27 0 0 01 Oct 2024
Training Large ASR Encoders with Differential Privacy Geeticka Chauhan Steve Chien Om Thakkar Abhradeep Thakurta Arun Narayanan 15 1 0 21 Sep 2024
Differentially Private Kernel Density Estimation Erzhi Liu Jerry Yao-Chieh Hu Alex Reneau Zhao Song Han Liu 56 3 0 03 Sep 2024
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates Puning Zhao Jiafei Wu Zhe Liu Chong Wang Rongfei Fan Qingming Li 40 1 0 19 Aug 2024
Better Gaussian Mechanism using Correlated Noise Christian Janos Lebeda 36 2 0 13 Aug 2024
GCON: Differentially Private Graph Convolutional Network via Objective Perturbation Jianxin Wei Yizheng Zhu Xiaokui Xiao Ergute Bao Yin Yang Kuntai Cai Beng Chin Ooi AAML 27 0 0 06 Jul 2024
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy Georgios Kaissis Stefan Kolek Borja Balle Jamie Hayes Daniel Rueckert 40 4 0 13 Jun 2024
Noise-Aware Differentially Private Regression via Meta-Learning Ossi Raisa Stratis Markou Matthew Ashman W. Bruinsma Marlon Tobaben Antti Honkela Richard E. Turner 57 1 0 12 Jun 2024
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition C. Lebeda Matthew Regehr Gautam Kamath Thomas Steinke 31 9 0 27 May 2024
You Can Use But Cannot Recognize: Preserving Visual Privacy in Deep Neural Networks Qiushi Li Yan Zhang Ju Ren Qi Li Yaoxue Zhang AAML PICV 31 22 0 05 Apr 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization Xinyu Tang Ashwinee Panda Milad Nasr Saeed Mahloujifar Prateek Mittal 44 18 0 09 Jan 2024
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer Junyuan Hong Jiachen T. Wang Chenhui Zhang Zhangheng Li Bo-wen Li Zhangyang Wang 36 29 0 27 Nov 2023
DP-TBART: A Transformer-based Autoregressive Model for Differentially Private Tabular Data Generation Rodrigo Castellon Achintya Gopal Brian Bloniarz David S. Rosenberg 4 7 0 19 Jul 2023
Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy Georgios Kaissis Jamie Hayes Alexander Ziller Daniel Rueckert AAML 16 11 0 08 Jul 2023
PILLAR: How to make semi-private learning more effective Francesco Pinto Yaxian Hu Fanny Yang Amartya Sanyal 25 11 0 06 Jun 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zi-Han Lin Sivakanth Gopi Janardhan Kulkarni Harsha Nori Sergey Yekhanin 33 36 0 24 May 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 15 39 0 14 Feb 2023
Private GANs, Revisited Alex Bie Gautam Kamath Guojun Zhang 4 14 0 06 Feb 2023
An Empirical Analysis of Fairness Notions under Differential Privacy Anderson Santana de Oliveira Caelin Kaplan Khawla Mallat Tanmay Chakraborty FedML 8 7 0 06 Feb 2023
Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imaging Soroosh Tayebi Arasteh Alexander Ziller Christiane Kuhl Marcus R. Makowski S. Nebelung R. Braren Daniel Rueckert Daniel Truhn Georgios Kaissis MedIm 19 17 0 03 Feb 2023
Straggler-Resilient Differentially-Private Decentralized Learning Yauhen Yakimenka Chung-Wei Weng Hsuan-Yin Lin E. Rosnes J. Kliewer 19 6 0 06 Dec 2022
Differentially Private Adaptive Optimization with Delayed Preconditioners Tian Li Manzil Zaheer Ziyu Liu Sashank J. Reddi H. B. McMahan Virginia Smith 26 10 0 01 Dec 2022
Differentially Private Image Classification from Features Harsh Mehta Walid Krichene Abhradeep Thakurta Alexey Kurakin Ashok Cutkosky 24 7 0 24 Nov 2022
Private Ad Modeling with DP-SGD Carson E. Denison Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Krishnagiri Narra Amer Sinha A. Varadarajan Chiyuan Zhang 17 14 0 21 Nov 2022
Learning to Generate Image Embeddings with User-level Differential Privacy Zheng Xu Maxwell D. Collins Yuxiao Wang Liviu Panait Sewoong Oh S. Augenstein Ting Liu Florian Schroff H. B. McMahan FedML 20 29 0 20 Nov 2022
Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning Christopher A. Choquette-Choo H. B. McMahan Keith Rush Abhradeep Thakurta 15 43 0 12 Nov 2022
Distributed DP-Helmet: Scalable Differentially Private Non-interactive Averaging of Single Layers Moritz Kirschte Sebastian Meiser Saman Ardalan Esfandiar Mohammadi FedML 19 0 0 03 Nov 2022
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe Xiang Yue Huseyin A. Inan Xuechen Li Girish Kumar Julia McAnallen Hoda Shajari Huan Sun David Levitan Robert Sim 17 79 0 25 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Y. Yang 37 20 0 18 Oct 2022
Fine-Tuning with Differential Privacy Necessitates an Additional Hyperparameter Search Yannis Cattan Christopher A. Choquette-Choo Nicolas Papernot Abhradeep Thakurta 13 20 0 05 Oct 2022
Differentially Private Optimization on Large Model at Small Cost Zhiqi Bu Yu-Xiang Wang Sheng Zha George Karypis 25 52 0 30 Sep 2022
When Does Differentially Private Learning Not Suffer in High Dimensions? Xuechen Li Daogao Liu Tatsunori Hashimoto Huseyin A. Inan Janardhan Kulkarni Y. Lee Abhradeep Thakurta 15 58 0 01 Jul 2022
Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das Satyen Kale Zheng Xu Tong Zhang Sujay Sanghavi 19 17 0 21 Jun 2022
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation Ljubomir Rokvic Panayiotis Danassis Sai Praneeth Karimireddy Boi Faltings TDI 15 1 0 23 May 2022
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy Zhiqi Bu J. Mao Shiyun Xu 131 47 0 21 May 2022
Improving Differentially Private SGD via Randomly Sparsified Gradients Junyi Zhu Matthew B. Blaschko 10 5 0 01 Dec 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
Not all noise is accounted equally: How differentially private learning benefits from large sampling rates Friedrich Dörmann Osvald Frisk L. Andersen Christian Fischer Pedersen FedML 44 25 0 12 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 144 348 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
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 220 510 0 11 Feb 2021