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Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 2,788 papers shown

Title
Privacy Preservation in Gen AI Applications S. M. Sani Ram Sundhar K Shaju Rakshana M Ganesh R Balavedhaa S Thiruvaazhi U 52 0 0 12 Apr 2025
FedFeat+: A Robust Federated Learning Framework Through Federated Aggregation and Differentially Private Feature-Based Classifier Retraining Mrityunjoy Gain Kitae Kim Avi Deb Raha Apurba Adhikary Eui-nam Huh Zhu Han Choong Seon Hong FedML 118 0 0 08 Apr 2025
Releasing Differentially Private Event Logs Using Generative Models Frederik Wangelik Majid Rafiei M. Pourbafrani Wil M.P. van der Aalst 79 0 0 08 Apr 2025
Your Image Generator Is Your New Private Dataset Nicolo Resmini Eugenio Lomurno Cristian Sbrolli Matteo Matteucci 130 0 0 06 Apr 2025
Structured Knowledge Accumulation: The Principle of Entropic Least Action in Forward-Only Neural Learning Bouarfa Mahi Quantiota 95 0 0 04 Apr 2025
Secure Generalization through Stochastic Bidirectional Parameter Updates Using Dual-Gradient Mechanism Shourya Goel Himanshi Tibrewal Anant Jain Anshul Pundhir Pravendra Singh FedML 127 0 0 03 Apr 2025
Tree-based Models for Vertical Federated Learning: A Survey Bingchen Qian Yuexiang Xie Yaliang Li Bolin Ding Jingren Zhou FedML 137 0 0 03 Apr 2025
Improving Efficiency in Federated Learning with Optimized Homomorphic Encryption Feiran Yang FedML 118 0 0 03 Apr 2025
From Easy to Hard: Building a Shortcut for Differentially Private Image Synthesis Kecen Li Chen Gong Xiaochen Li Yuzhong Zhao Xinwen Hou Tianhao Wang 106 1 0 02 Apr 2025
Benchmarking Federated Machine Unlearning methods for Tabular Data Chenguang Xiao Abhirup Ghosh Han Wu Shuo Wang Diederick van Thiel MU 78 0 0 01 Apr 2025
Forward Learning with Differential Privacy Mingqian Feng Zeliang Zhang Jinyang Jiang Yijie Peng Chenliang Xu 104 0 0 01 Apr 2025
DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation Chengkun Wei Weixian Li Chen Gong Wenzhi Chen 117 1 0 29 Mar 2025
Instance-Level Data-Use Auditing of Visual ML Models Zonghao Huang Neil Zhenqiang Gong Michael K. Reiter MLAU 110 0 0 28 Mar 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 107 0 0 27 Mar 2025
Federated Learning with Differential Privacy: An Utility-Enhanced Approach Kanishka Ranaweera Dinh C. Nguyen P. Pathirana David B. Smith Ming Ding Thierry Rakotoarivelo A. Seneviratne FedML 102 0 0 27 Mar 2025
Bayesian Pseudo Posterior Mechanism for Differentially Private Machine Learning Robert Chew Matthew R. Williams Elan A. Segarra Alexander J. Preiss Amanda Konet T. Savitsky 103 0 0 27 Mar 2025
Multi-Objective Optimization for Privacy-Utility Balance in Differentially Private Federated Learning Kanishka Ranaweera David B. Smith P. Pathirana Ming Ding Thierry Rakotoarivelo A. Seneviratne FedML 80 0 0 27 Mar 2025
AdvSGM: Differentially Private Graph Learning via Adversarial Skip-gram Model Sen Zhang Qingqing Ye Haibo Hu Jianliang Xu 76 0 0 27 Mar 2025
Purifying Approximate Differential Privacy with Randomized Post-processing Yingyu Lin Erchi Wang Yi-An Ma Yu-Xiang Wang 77 0 0 27 Mar 2025
TS-Inverse: A Gradient Inversion Attack Tailored for Federated Time Series Forecasting Models Caspar Meijer Jiyue Huang Shreshtha Sharma Elena Lazovik Lydia Y. Chen AI4TS 79 0 0 26 Mar 2025
Generating Synthetic Data with Formal Privacy Guarantees: State of the Art and the Road Ahead Viktor Schlegel Anil A Bharath Zilong Zhao Kevin Yee 125 0 0 26 Mar 2025
OFL: Opportunistic Federated Learning for Resource-Heterogeneous and Privacy-Aware Devices Yunlong Mao Mingyang Niu Ziqin Dang Chengxi Li Hanning Xia Yuejuan Zhu Haoyu Bian Yuan Zhang Jingyu Hua Sheng Zhong FedML 99 0 0 19 Mar 2025
Defending Against Gradient Inversion Attacks for Biomedical Images via Learnable Data Perturbation Shiyi Jiang F. Firouzi Krishnendu Chakrabarty AAML MedIm 99 1 0 19 Mar 2025
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis Chen Gong Kecen Li Zinan Lin Tianhao Wang 226 5 0 18 Mar 2025
Empirical Calibration and Metric Differential Privacy in Language Models Pedro Faustini Natasha Fernandes Annabelle McIver Mark Dras 104 0 0 18 Mar 2025
An Optimization Framework for Differentially Private Sparse Fine-Tuning Mehdi Makni Kayhan Behdin Gabriel Afriat Zheng Xu Sergei Vassilvitskii Natalia Ponomareva Hussein Hazimeh Rahul Mazumder 127 0 0 17 Mar 2025
BLIA: Detect model memorization in binary classification model through passive Label Inference attack Mohammad Wahiduzzaman Khan Sheng Chen Ilya Mironov Leizhen Zhang Rabib Noor 163 0 0 17 Mar 2025
Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs Bowen Tan Zheng Xu Eric P. Xing Zhiting Hu Shanshan Wu SyDa 194 3 0 16 Mar 2025
Empirical Privacy Variance Yuzheng Hu Fan Wu Ruicheng Xian Yuhang Liu Lydia Zakynthinou Pritish Kamath Chiyuan Zhang David A. Forsyth 156 0 0 16 Mar 2025
PREAMBLE: Private and Efficient Aggregation via Block Sparse Vectors Hilal Asi Vitaly Feldman Hannah Keller G. Rothblum Kunal Talwar FedML 129 1 0 14 Mar 2025
DP-GPL: Differentially Private Graph Prompt Learning Jing Xu Franziska Boenisch Iyiola Emmanuel Olatunji Adam Dziedzic AAML 115 0 0 13 Mar 2025
$(\varepsilon, δ)$ Considered Harmful: Best Practices for Reporting Differential Privacy Guarantees Juan Felipe Gomez B. Kulynych G. Kaissis Jamie Hayes Borja Balle Antti Honkela 117 0 0 13 Mar 2025
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates Chuanyin Wang Yifei Zhang Neng Gao Qiang Luo FedML 211 0 0 12 Mar 2025
Technical Insights and Legal Considerations for Advancing Federated Learning in Bioinformatics Daniele Malpetti Marco Scutari Francesco Gualdi Jessica van Setten Sander van der Laan Saskia Haitjema Aaron Mark Lee Isabelle Hering Francesca Mangili FedML AI4CE 181 1 0 12 Mar 2025
AgentDAM: Privacy Leakage Evaluation for Autonomous Web Agents Arman Zharmagambetov Chuan Guo Ivan Evtimov Maya Pavlova Ruslan Salakhutdinov Kamalika Chaudhuri LLMAG 149 8 0 12 Mar 2025
A Comprehensive Review on Understanding the Decentralized and Collaborative Approach in Machine Learning S. Saif Md Jahirul Islam Md. Zihad Bin Jahangir Parag Biswas Abdur Rashid Md Abdullah Al Nasim Kishor Datta Gupta 104 2 0 12 Mar 2025
PoisonedParrot: Subtle Data Poisoning Attacks to Elicit Copyright-Infringing Content from Large Language Models Michael-Andrei Panaitescu-Liess Pankayaraj Pathmanathan Yigitcan Kaya Zora Che Bang An Sicheng Zhu Aakriti Agrawal Furong Huang AAML 130 2 0 10 Mar 2025
How Well Can Differential Privacy Be Audited in One Run? Amit Keinan Moshe Shenfeld Katrina Ligett 149 2 0 10 Mar 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond Qiongxiu Li Xiaoyu Luo Yiyi Chen Johannes Bjerva 266 2 0 10 Mar 2025
From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges Qiongxiu Li Wenrui Yu Yufei Xia Jun Pang FedML 107 2 0 10 Mar 2025
ConcreTizer: Model Inversion Attack via Occupancy Classification and Dispersion Control for 3D Point Cloud Restoration Youngseok Kim Sunwook Hwang Hyung-Sin Kim S. Bahk DiffM 3DPC 95 0 0 10 Mar 2025
Data Efficient Subset Training with Differential Privacy Ninad Jayesh Gandhi Moparthy Venkata Subrahmanya Sri Harsha 108 0 0 09 Mar 2025
Privacy Auditing of Large Language Models Ashwinee Panda Xinyu Tang Milad Nasr Christopher A. Choquette-Choo Prateek Mittal PILM 149 12 0 09 Mar 2025
Do Fairness Interventions Come at the Cost of Privacy: Evaluations for Binary Classifiers Huan Tian Guangsheng Zhang Bo Liu Tianqing Zhu Ming Ding Wanlei Zhou 115 1 0 08 Mar 2025
Mitigating Memorization in LLMs using Activation Steering Manan Suri Nishit Anand Amisha Bhaskar LLMSV 126 3 0 08 Mar 2025
DP-GTR: Differentially Private Prompt Protection via Group Text Rewriting Mingchen Li Heng Fan Song Fu Junhua Ding Yunhe Feng 86 0 0 06 Mar 2025
Differentially Private Learners for Heterogeneous Treatment Effects Maresa Schröder Valentyn Melnychuk Stefan Feuerriegel CML 171 2 0 05 Mar 2025
SpinML: Customized Synthetic Data Generation for Private Training of Specialized ML Models Jiang Zhang Rohan Sequeira Konstantinos Psounis SyDa 127 0 0 05 Mar 2025
Privacy and Accuracy-Aware AI/ML Model Deduplication Hong Guan Lei Yu Lixi Zhou Li Xiong Kanchan Chowdhury Lulu Xie Xusheng Xiao Jia Zou 90 0 0 04 Mar 2025
Leveraging Randomness in Model and Data Partitioning for Privacy Amplification Andy Dong Wei-Ning Chen Ayfer Özgür FedML 124 1 0 04 Mar 2025