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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
Atlas-X Equity Financing: Unlocking New Methods to Securely Obfuscate Axe Inventory Data Based on Differential Privacy Antigoni Polychroniadou Gabriele Cipriani Richard Hua T. Balch 67 0 0 10 Apr 2024
Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability Fatima Ezzeddine Mirna Saad Omran Ayoub Davide Andreoletti M. Gjoreski Ihab Sbeity Marc Langheinrich Silvia Giordano 61 3 0 09 Apr 2024
Privacy Preserving Prompt Engineering: A Survey Kennedy Edemacu Xintao Wu 138 23 0 09 Apr 2024
Advances in Differential Privacy and Differentially Private Machine Learning Saswat Das Subhankar Mishra 92 4 0 06 Apr 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 90 25 0 05 Apr 2024
Faraday: Synthetic Smart Meter Generator for the smart grid Sheng Chai Gus Chadney 81 6 0 05 Apr 2024
Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning Hongsheng Hu Shuo Wang Tian Dong Minhui Xue AAML 93 28 0 04 Apr 2024
Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds Kamalika Chaudhuri Chuan Guo Laurens van der Maaten Saeed Mahloujifar M. Tygert 77 1 0 03 Apr 2024
A Unified Membership Inference Method for Visual Self-supervised Encoder via Part-aware Capability Jie Zhu Jirong Zha Ding Li Leye Wang 110 8 0 03 Apr 2024
Digital Forgetting in Large Language Models: A Survey of Unlearning Methods Alberto Blanco-Justicia N. Jebreel Benet Manzanares-Salor David Sánchez Josep Domingo-Ferrer Guillem Collell Kuan Eeik Tan KELM MU 117 22 0 02 Apr 2024
Incentives in Private Collaborative Machine Learning Rachael Hwee Ling Sim Yehong Zhang Nghia Hoang Xinyi Xu K. H. Low Patrick Jaillet 106 5 0 02 Apr 2024
AAA: an Adaptive Mechanism for Locally Differential Private Mean Estimation Fei Wei Ergute Bao Xiaokui Xiao Yin Yang Bolin Ding 97 4 0 02 Apr 2024
SoK: A Review of Differentially Private Linear Models For High-Dimensional Data Amol Khanna Edward Raff Nathan Inkawhich 97 5 0 01 Apr 2024
Towards Memorization-Free Diffusion Models Chen Chen Daochang Liu Chang Xu VLM 111 34 0 01 Apr 2024
Privacy Re-identification Attacks on Tabular GANs Abdallah Alshantti Adil Rasheed Frank Westad AAML 93 4 0 31 Mar 2024
A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures Thanh Tam Nguyen T. T. Huynh Zhao Ren Thanh Toan Nguyen Phi Le Nguyen Hongzhi Yin Quoc Viet Hung Nguyen 182 8 0 31 Mar 2024
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models Shanglun Feng Florian Tramèr SILM 100 21 0 30 Mar 2024
How Private are DP-SGD Implementations? Lynn Chua Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 114 14 0 26 Mar 2024
Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion Hossein Souri Arpit Bansal Hamid Kazemi Liam H. Fowl Aniruddha Saha Jonas Geiping Andrew Gordon Wilson Rama Chellappa Tom Goldstein Micah Goldblum SILM DiffM 77 1 0 25 Mar 2024
TablePuppet: A Generic Framework for Relational Federated Learning Lijie Xu Chulin Xie Yiran Guo Gustavo Alonso Yue Liu Guoliang Li Wei Wang Wentao Wu Ce Zhang FedML 106 0 0 23 Mar 2024
Differentially Private Next-Token Prediction of Large Language Models James Flemings Meisam Razaviyayn Murali Annavaram 118 11 0 22 Mar 2024
Differentially Private Ad Conversion Measurement John Delaney Badih Ghazi Charlie Harrison Christina Ilvento Ravi Kumar Pasin Manurangsi Martin Pal Karthik Prabhakar Mariana Raykova 60 4 0 22 Mar 2024
Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures S. V. Dibbo Adam Breuer Juston S. Moore Michael Teti AAML 87 5 0 21 Mar 2024
DP-RDM: Adapting Diffusion Models to Private Domains Without Fine-Tuning Jonathan Lebensold Maziar Sanjabi Pietro Astolfi Adriana Romero Soriano Kamalika Chaudhuri Mike Rabbat Chuan Guo DiffM 79 5 0 21 Mar 2024
Does Differentially Private Synthetic Data Lead to Synthetic Discoveries? Ileana Montoya Perez P. Movahedi Valtteri Nieminen A. Airola T. Pahikkala 84 6 0 20 Mar 2024
Provable Privacy with Non-Private Pre-Processing Yaxian Hu Amartya Sanyal Bernhard Schölkopf 67 2 0 19 Mar 2024
Improving LoRA in Privacy-preserving Federated Learning Youbang Sun Zitao Li Yaliang Li Bolin Ding 104 86 0 18 Mar 2024
Smooth Sensitivity for Learning Differentially-Private yet Accurate Rule Lists Timothée Ly Julien Ferry Marie-José Huguet Sébastien Gambs Ulrich Aïvodji 60 0 0 18 Mar 2024
Budget Recycling Differential Privacy Bo Jiang Jian Du Sagar Shamar Qiang Yan 88 2 0 18 Mar 2024
Pencil: Private and Extensible Collaborative Learning without the Non-Colluding Assumption Xuanqi Liu Zhuotao Liu Qi Li Ke Xu Mingwei Xu 78 8 0 17 Mar 2024
Programming Frameworks for Differential Privacy Marco Gaboardi Michael Hay Salil P. Vadhan 73 1 0 17 Mar 2024
PreCurious: How Innocent Pre-Trained Language Models Turn into Privacy Traps Ruixuan Liu Tianhao Wang Yang Cao Li Xiong AAML SILM 187 20 0 14 Mar 2024
Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk Zhangheng Li Junyuan Hong Yue Liu Zhangyang Wang DiffM 87 18 0 14 Mar 2024
Bridging Quantum Computing and Differential Privacy: Insights into Quantum Computing Privacy Yusheng Zhao Hui Zhong Xinyue Zhang Yuqing Li Chi Zhang Miao Pan 90 3 0 14 Mar 2024
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains Lei Wang Jieming Bian Letian Zhang Chong Chen Jie Xu 90 9 0 14 Mar 2024
Efficiently Computing Similarities to Private Datasets A. Backurs Zinan Lin S. Mahabadi Sandeep Silwal Jakub Tarnawski 98 6 0 13 Mar 2024
Second-Order Information Matters: Revisiting Machine Unlearning for Large Language Models Kang Gu Md Rafi Ur Rashid Najrin Sultana Shagufta Mehnaz MU 102 7 0 13 Mar 2024
SoK: Reducing the Vulnerability of Fine-tuned Language Models to Membership Inference Attacks Guy Amit Abigail Goldsteen Ariel Farkash AAML 72 7 0 13 Mar 2024
SoK: Can Trajectory Generation Combine Privacy and Utility? Erik Buchholz A. Abuadbba Shuo Wang Surya Nepal S. Kanhere 97 7 0 12 Mar 2024
Visual Privacy Auditing with Diffusion Models Kristian Schwethelm Johannes Kaiser Moritz Knolle Daniel Rueckert Daniel Rueckert Alexander Ziller DiffM AAML 103 0 0 12 Mar 2024
DP-TLDM: Differentially Private Tabular Latent Diffusion Model Chaoyi Zhu Jiayi Tang Juan F. Pérez Marten van Dijk Marten van Dijk 111 5 0 12 Mar 2024
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That? Egor Zverev Sahar Abdelnabi Soroush Tabesh Mario Fritz Christoph H. Lampert 130 31 0 11 Mar 2024
DP-TabICL: In-Context Learning with Differentially Private Tabular Data Alycia N. Carey Karuna Bhaila Kennedy Edemacu Xintao Wu 122 8 0 08 Mar 2024
Federated Joint Learning of Robot Networks in Stroke Rehabilitation Xinyu Jiang Yibei Guo Mengsha Hu Ruoming Jin Hai Phan Jay Alberts Rui Liu 39 0 0 08 Mar 2024
EdgeLeakage: Membership Information Leakage in Distributed Edge Intelligence Systems Kongyang Chen Yi Lin Hui Luo Bing Mi Yatie Xiao Chao Ma Jorge Sá Silva 47 3 0 08 Mar 2024
Privacy Amplification for the Gaussian Mechanism via Bounded Support Shengyuan Hu Saeed Mahloujifar Virginia Smith Kamalika Chaudhuri Chuan Guo FedML 84 1 0 07 Mar 2024
Privacy-preserving Fine-tuning of Large Language Models through Flatness Tiejin Chen Longchao Da Huixue Zhou Pingzhi Li Kaixiong Zhou Tianlong Chen Hua Wei 78 5 0 07 Mar 2024
SPEAR:Exact Gradient Inversion of Batches in Federated Learning Dimitar I. Dimitrov Maximilian Baader Mark Niklas Muller Martin Vechev FedML 92 8 0 06 Mar 2024
A general approach to enhance the survivability of backdoor attacks by decision path coupling Yufei Zhao Dingji Wang Bihuan Chen Ziqian Chen Xin Peng AAML 76 0 0 05 Mar 2024
DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training Zihao Wang Rui Zhu Dongruo Zhou Zhikun Zhang John C. Mitchell Haixu Tang Wenyuan Xu AAML 90 6 0 05 Mar 2024