Papers citing 'AdaCliP: Adaptive Clipping for Private SGD'

Title
Rethinking Layer-wise Gaussian Noise Injection: Bridging Implicit Objectives and Privacy Budget Allocation Qifeng Tan Shusen Yang Xuebin Ren Yikai Zhang 123 0 0 04 Sep 2025
Towards Reliable and Generalizable Differentially Private Machine Learning (Extended Version) Wenxuan Bao Vincent Bindschaedler AAML 228 0 0 21 Aug 2025
Efficient Differentially Private Fine-Tuning of LLMs via Reinforcement Learning Afshin Khadangi Amir Sartipi Xiaohui Wu Ramin Bahmani Gilbert Fridgen 116 0 0 30 Jul 2025
GeoClip: Geometry-Aware Clipping for Differentially Private SGD Atefeh Gilani Naima Tasnim Lalitha Sankar O. Kosut 168 1 0 06 Jun 2025
Fast Fourier Transform-Based Spectral and Temporal Gradient Filtering for Differential Privacy Hyeju Shin Kyudan Jung Kyudan Jung Seongwon Yun 315 0 0 07 May 2025
Adaptive Clipping for Privacy-Preserving Few-Shot Learning: Enhancing Generalization with Limited Data Kanishka Ranaweera Dinh C. Nguyen P. Pathirana David B. Smith Ming Ding Thierry Rakotoarivelo A. Seneviratne 199 1 0 27 Mar 2025
Video-DPRP: A Differentially Private Approach for Visual Privacy-Preserving Video Human Activity Recognition Allassan Tchangmena A Nken Susan Mckeever Peter Corcoran Ihsan Ullah PICV 362 0 0 03 Mar 2025
Structure-Preference Enabled Graph Embedding Generation under Differential PrivacyIEEE International Conference on Data Engineering (ICDE), 2025 Sen Zhang Qingqing Ye Haibo Hu 198 1 0 08 Jan 2025
SeqMIA: Sequential-Metric Based Membership Inference Attack Hao Li Zheng Li Siyuan Wu Chengrui Hu Yutong Ye Min Zhang Dengguo Feng Yang Zhang 188 24 0 21 Jul 2024
PCDP-SGD: Improving the Convergence of Differentially Private SGD via Projection in Advance Haichao Sha Ruixuan Liu Yi-xiao Liu Hong Chen 247 2 0 06 Dec 2023
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and FilteringIEEE Symposium on Security and Privacy (IEEE S&P), 2023 Ce Feng Nuo Xu Wujie Wen Parv Venkitasubramaniam Caiwen Ding 157 5 0 25 Jul 2023
PLAN: Variance-Aware Private Mean EstimationProceedings on Privacy Enhancing Technologies (PoPETs), 2023 Martin Aumüller C. Lebeda Boel Nelson Rasmus Pagh FedML 232 5 0 14 Jun 2023
DPMLBench: Holistic Evaluation of Differentially Private Machine LearningConference on Computer and Communications Security (CCS), 2023 Chengkun Wei Ming-Hui Zhao Zhikun Zhang Min Chen Wenlong Meng Bodong Liu Yuan-shuo Fan Wenzhi Chen 345 16 0 10 May 2023
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph EmbeddingThe Web Conference (WWW), 2023 Yuke Hu Wei Liang Ruofan Wu Kai Y. Xiao Weiqiang Wang Xiaochen Li Jinfei Liu Zhan Qin 172 16 0 06 Apr 2023
U-Clip: On-Average Unbiased Stochastic Gradient Clipping Bryn Elesedy Marcus Hutter 163 2 0 06 Feb 2023
Mitigating Memorization of Noisy Labels by Clipping the Model PredictionInternational Conference on Machine Learning (ICML), 2022 Jianguo Huang Huiping Zhuang Renchunzi Xie Lei Feng Gang Niu Bo An Shouqing Yang VLM NoLa 446 43 0 08 Dec 2022
Exploring the Limits of Differentially Private Deep Learning with Group-wise ClippingInternational Conference on Learning Representations (ICLR), 2022 Jiyan He Xuechen Li Da Yu Huishuai Zhang Janardhan Kulkarni Y. Lee A. Backurs Nenghai Yu Jiang Bian 333 57 0 03 Dec 2022
Differentially Private Learning with Per-Sample Adaptive ClippingAAAI Conference on Artificial Intelligence (AAAI), 2022 Tianyu Xia Shuheng Shen Su Yao Xinyi Fu Ke Xu Xiaolong Xu Xingbo Fu 459 27 0 01 Dec 2022
Differentially Private Image Classification from Features Harsh Mehta Walid Krichene Abhradeep Thakurta Alexey Kurakin Ashok Cutkosky 223 10 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 359 15 0 21 Nov 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance SamplingConference on Computer and Communications Security (CCS), 2022 Jianxin Wei Ergute Bao X. Xiao Yifan Yang 336 28 0 18 Oct 2022
Dynamic Global Sensitivity for Differentially Private Contextual BanditsACM Conference on Recommender Systems (RecSys), 2022 Huazheng Wang Dave Zhao Hongning Wang 195 6 0 30 Aug 2022
(Nearly) Optimal Private Linear Regression via Adaptive Clipping Prateeksha Varshney Abhradeep Thakurta Prateek Jain 172 9 0 11 Jul 2022
Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization Xiaodong Yang Huishuai Zhang Wei Chen Tie-Yan Liu 185 40 0 27 Jun 2022
On Privacy and Personalization in Cross-Silo Federated LearningNeural Information Processing Systems (NeurIPS), 2022 Ziyu Liu Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 279 69 0 16 Jun 2022
Disparate Impact in Differential Privacy from Gradient MisalignmentInternational Conference on Learning Representations (ICLR), 2022 Maria S. Esipova Atiyeh Ashari Ghomi Yaqiao Luo Jesse C. Cresswell 259 41 0 15 Jun 2022
Automatic Clipping: Differentially Private Deep Learning Made Easier and StrongerNeural Information Processing Systems (NeurIPS), 2022 Zhiqi Bu Yu Wang Sheng Zha George Karypis 550 96 0 14 Jun 2022
Differentially Private Covariance RevisitedNeural Information Processing Systems (NeurIPS), 2022 Wei Dong Yuting Liang K. Yi FedML 306 19 0 28 May 2022
Large Scale Transfer Learning for Differentially Private Image Classification Harsh Mehta Abhradeep Thakurta Alexey Kurakin Ashok Cutkosky 212 48 0 06 May 2022
Nonlinear gradient mappings and stochastic optimization: A general framework with applications to heavy-tail noiseSIAM Journal on Optimization (SIAM J. Optim.), 2022 D. Jakovetić Dragana Bajović Anit Kumar Sahu S. Kar Nemanja Milošević Dusan Stamenkovic 197 20 0 06 Apr 2022
Statistic Selection and MCMC for Differentially Private Bayesian EstimationStatistics and computing (Stat. Comput.), 2022 Barış Alparslan S. Yıldırım 227 3 0 24 Mar 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence)Neural Information Processing Systems (NeurIPS), 2022 Jiayuan Ye Reza Shokri FedML 262 56 0 10 Mar 2022
Private Adaptive Optimization with Side InformationInternational Conference on Machine Learning (ICML), 2022 Tian Li Manzil Zaheer Sashank J. Reddi Virginia Smith 168 43 0 12 Feb 2022
Toward Training at ImageNet Scale with Differential Privacy Alexey Kurakin Shuang Song Steve Chien Roxana Geambasu Seth Neel Abhradeep Thakurta 304 111 0 28 Jan 2022
Gradient Leakage Attack Resilient Deep LearningIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2021 Wenqi Wei Ling Liu SILM PILM AAML 178 61 0 25 Dec 2021
Improving Differentially Private SGD via Randomly Sparsified Gradients Junyi Zhu Matthew B. Blaschko 363 7 0 01 Dec 2021
Universal Private EstimatorsACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS), 2021 Wei Dong K. Yi 309 22 0 04 Nov 2021
Dynamic Differential-Privacy Preserving SGD Jian Du Song Li Xiangyi Chen Siheng Chen Mingyi Hong 172 41 0 30 Oct 2021
Differentially Private Coordinate Descent for Composite Empirical Risk MinimizationInternational Conference on Machine Learning (ICML), 2021 Paul Mangold A. Bellet Joseph Salmon Marc Tommasi 453 16 0 22 Oct 2021
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy Anda Cheng Jiaxing Wang Xi Sheryl Zhang Qiang Chen Peisong Wang Jian Cheng 261 33 0 16 Oct 2021
NanoBatch Privacy: Enabling fast Differentially Private learning on the IPU Edward H. Lee M. M. Krell Alexander Tsyplikhin Victoria Rege E. Colak Kristen W. Yeom FedML 135 0 0 24 Sep 2021
Efficient Hyperparameter Optimization for Differentially Private Deep Learning Aman Priyanshu Rakshit Naidu Fatemehsadat Mireshghallah Mohammad Malekzadeh 178 9 0 09 Aug 2021
Large-Scale Differentially Private BERT Rohan Anil Badih Ghazi Vineet Gupta Ravi Kumar Pasin Manurangsi 223 146 0 03 Aug 2021
Private Adaptive Gradient Methods for Convex OptimizationInternational Conference on Machine Learning (ICML), 2021 Hilal Asi John C. Duchi Alireza Fallah O. Javidbakht Kunal Talwar 198 58 0 25 Jun 2021
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential PrivacyInternational Conference on Machine Learning (ICML), 2021 Xinwei Zhang Xiangyi Chen Min-Fong Hong Zhiwei Steven Wu Jinfeng Yi FedML 191 118 0 25 Jun 2021
Instance-optimal Mean Estimation Under Differential PrivacyNeural Information Processing Systems (NeurIPS), 2021 Ziyue Huang Yuting Liang K. Yi 175 65 0 01 Jun 2021
Quantifying and Localizing Usable Information Leakage from Neural Network Gradients Fan Mo Anastasia Borovykh Mohammad Malekzadeh Soteris Demetriou Deniz Gündüz Hamed Haddadi FedML 175 5 0 28 May 2021
DataLens: Scalable Privacy Preserving Training via Gradient Compression and AggregationConference on Computer and Communications Security (CCS), 2021 Wei Ping Fan Wu Yunhui Long Luka Rimanic Ce Zhang Yue Liu FedML 594 73 0 20 Mar 2021
Label Leakage and Protection in Two-party Split LearningInternational Conference on Learning Representations (ICLR), 2021 Oscar Li Jiankai Sun Xin Yang Weihao Gao Hongyi Zhang Junyuan Xie Virginia Smith Chong-Jun Wang FedML 299 162 0 17 Feb 2021
N-grams Bayesian Differential Privacy Osman Ramadan James Withers Douglas Orr 101 0 0 29 Jan 2021