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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
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 103 0 0 03 Mar 2025
Heterogeneity Matters even More in Distributed Learning: Study from Generalization Perspective Masoud Kavian Romain Chor Milad Sefidgaran Abdellatif Zaidi FedML 129 1 0 03 Mar 2025
AMUN: Adversarial Machine UNlearning A. Boroojeny Hari Sundaram Varun Chandrasekaran MU AAML 94 1 0 02 Mar 2025
Towards hyperparameter-free optimization with differential privacy Zhiqi Bu Ruixuan Liu 89 2 0 02 Mar 2025
CBW: Towards Dataset Ownership Verification for Speaker Verification via Clustering-based Backdoor Watermarking Yiming Li Kaiying Yan Shuo Shao Tongqing Zhai Shu-Tao Xia Zhan Qin D. Tao AAML 381 0 0 02 Mar 2025
Tokens for Learning, Tokens for Unlearning: Mitigating Membership Inference Attacks in Large Language Models via Dual-Purpose Training Toan Tran Ruixuan Liu Li Xiong MU 126 1 0 27 Feb 2025
Climate And Resource Awareness is Imperative to Achieving Sustainable AI (and Preventing a Global AI Arms Race) Pedram Bakhtiarifard Pınar Tözün Christian Igel Raghavendra Selvan 130 1 0 27 Feb 2025
Gatekeeper: Improving Model Cascades Through Confidence Tuning Stephan Rabanser Nathalie Rauschmayr Achin Kulshrestha Petra Poklukar Wittawat Jitkrittum Sean Augenstein Congchao Wang Federico Tombari 123 1 0 26 Feb 2025
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models Yu He Boheng Li Lu Liu Zhongjie Ba Wei Dong Yiming Li Zhan Qin Kui Ren Chong Chen MIALM 188 3 0 26 Feb 2025
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning Guikun Chen Xu Zhang Yue Yang Yong Liu Yi Yang Wenguan Wang 98 0 0 26 Feb 2025
An Improved Privacy and Utility Analysis of Differentially Private SGD with Bounded Domain and Smooth Losses Hao Liang Wentao Zhang Xinlei He Kaishun He Hong Xing 131 0 0 25 Feb 2025
FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk Tianyu Zhao Mahmoud Srewa Salma Elmalaki 172 1 0 25 Feb 2025
Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning Raghav Singhal Kaustubh Ponkshe Rohit Vartak Lav R. Varshney Praneeth Vepakomma FedML 140 4 0 24 Feb 2025
Differential privacy guarantees of Markov chain Monte Carlo algorithms Andrea Bertazzi Tim Johnston Gareth O. Roberts Alain Durmus 79 0 0 24 Feb 2025
When to Forget? Complexity Trade-offs in Machine Unlearning Martin Van Waerebeke Marco Lorenzi Giovanni Neglia Kevin Scaman MU 99 0 0 24 Feb 2025
Subspace Recovery in Winsorized PCA: Insights into Accuracy and Robustness Sangil Han Kyoowon Kim Sungkyu Jung 83 1 0 23 Feb 2025
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification Anan Kabaha Dana Drachsler-Cohen AAML 118 0 0 23 Feb 2025
Can Large Vision-Language Models Detect Images Copyright Infringement from GenAI? Qipan Xu Ziyi Wang Xiaoxiao He Ligong Han Ruixiang Tang 61 1 0 23 Feb 2025
RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis Jianwei Wang Junyao Yang Haoran Li Huiping Zhuang Cen Chen Huiping Zhuang SyDa 101 0 0 23 Feb 2025
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments Kaixiang Zhao Lincan Li Kaize Ding Neil Zhenqiang Gong Yue Zhao Yushun Dong AAML 84 3 0 22 Feb 2025
Towards User-level Private Reinforcement Learning with Human Feedback Jing Zhang Mingxi Lei Meng Ding Mengdi Li Zihang Xiang Difei Xu Jinhui Xu Di Wang 119 4 0 22 Feb 2025
$Approximate Differential Privacy of the $\ell_2$ Mechanism$ Approximate Differential Privacy of the $\ell_2$ Mechanism Matthew Joseph Alex Kulesza Alexander Yu 64 0 0 21 Feb 2025
PPC-GPT: Federated Task-Specific Compression of Large Language Models via Pruning and Chain-of-Thought Distillation Tao Fan Guoqiang Ma Yuanfeng Song Lixin Fan Kai Chen Qiang Yang 90 1 0 21 Feb 2025
Smoothed Normalization for Efficient Distributed Private Optimization Egor Shulgin Sarit Khirirat Peter Richtárik FedML 149 0 0 20 Feb 2025
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text Matthieu Meeus Lukas Wutschitz Santiago Zanella Béguelin Shruti Tople Reza Shokri 216 2 0 19 Feb 2025
RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models Tanqiu Jiang Changjiang Li Fenglong Ma Ting Wang 128 1 0 18 Feb 2025
R.R.: Unveiling LLM Training Privacy through Recollection and Ranking Wenlong Meng Zhenyuan Guo Lenan Wu Chen Gong Wenyan Liu Weixian Li Chengkun Wei Wenzhi Chen PILM 69 1 0 18 Feb 2025
Does Training with Synthetic Data Truly Protect Privacy? Yunpeng Zhao Jie Zhang 150 2 0 18 Feb 2025
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning Saber Malekmohammadi Yaoliang Yu Yang Cao FedML 178 6 0 17 Feb 2025
Vertical Federated Learning in Practice: The Good, the Bad, and the Ugly Zhaomin Wu Zhen Qin Junyi Hou Haodong Zhao Qinbin Li Bingsheng He Lixin Fan FedML 124 2 0 12 Feb 2025
Trustworthy AI: Safety, Bias, and Privacy -- A Survey Xingli Fang Jianwei Li Varun Mulchandani Jung-Eun Kim 101 0 0 11 Feb 2025
Privacy-Preserving Dataset Combination Keren Fuentes Mimee Xu Irene Chen 130 0 0 09 Feb 2025
Stochastic Forward-Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets Haoye Lu Qifan Wu Yaoliang Yu DiffM 131 2 0 08 Feb 2025
Adversarial Machine Learning: Attacks, Defenses, and Open Challenges Pranav K Jha AAML 96 0 0 08 Feb 2025
Training Set Reconstruction from Differentially Private Forests: How Effective is DP? Alice Gorgé Julien Ferry Sébastien Gambs Thibaut Vidal 100 0 0 07 Feb 2025
Learning with Differentially Private (Sliced) Wasserstein Gradients David Rodríguez-Vítores Clément Lalanne Jean-Michel Loubes FedML 124 0 0 03 Feb 2025
On the Impact of Noise in Differentially Private Text Rewriting Stephen Meisenbacher Maulik Chevli Florian Matthes 122 0 0 31 Jan 2025
Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run Zihang Xiang Tianhao Wang Di Wang 87 5 0 29 Jan 2025
Differential Privacy with Higher Utility by Exploiting Coordinate-wise Disparity: Laplace Mechanism Can Beat Gaussian in High Dimensions Gokularam Muthukrishnan Sheetal Kalyani 183 1 0 28 Jan 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Kaiyuan Zhang Siyuan Cheng Guangyu Shen Bruno Ribeiro Shengwei An Pin-Yu Chen Xinming Zhang Ninghui Li 358 2 0 28 Jan 2025
SoK: What Makes Private Learning Unfair? Kai Yao Marc Juarez 90 0 0 24 Jan 2025
A Selective Homomorphic Encryption Approach for Faster Privacy-Preserving Federated Learning Abdulkadir Korkmaz Praveen Rao FedML 163 1 0 22 Jan 2025
TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data P. Tiwald Ivona Krchova Andrey Sidorenko Mariana Vargas-Vieyra Mario Scriminaci Michael Platzer 167 3 0 21 Jan 2025
Episodic memory in AI agents poses risks that should be studied and mitigated Chad DeChant 147 4 0 20 Jan 2025
Flash: A Hybrid Private Inference Protocol for Deep CNNs with High Accuracy and Low Latency on CPU H. Roh Jinsu Yeo Yeongil Ko Gu-Yeon Wei David Brooks Woo-Seok Choi 188 2 0 20 Jan 2025
GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models Jiadong Lou Xu Yuan Rui Zhang Xingliang Yuan Neil Gong N. Tzeng AAML 107 1 0 19 Jan 2025
Modeling Neural Networks with Privacy Using Neural Stochastic Differential Equations Sanghyun Hong Fan Wu A. Gruber Kookjin Lee 94 0 0 12 Jan 2025
Private Selection with Heterogeneous Sensitivities Daniela Antonova Allegra Laro Audra McMillan Lorenz Wolf 172 0 0 10 Jan 2025
Structure-Preference Enabled Graph Embedding Generation under Differential Privacy Sen Zhang Qingqing Ye Haibo Hu 102 0 0 08 Jan 2025
Lossless Privacy-Preserving Aggregation for Decentralized Federated Learning Xiaoye Miao Bin Li Yangyang Wu Meng Xi Xinkui Zhao 90 0 0 08 Jan 2025