Title
Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients Weijun Li Qiongkai Xu Mark Dras PILM 32 1 0 03 Jun 2024
Delving into Differentially Private Transformer Youlong Ding Xueyang Wu Yining Meng Yonggang Luo Hao Wang Weike Pan 36 5 0 28 May 2024
Laboratory-Scale AI: Open-Weight Models are Competitive with ChatGPT Even in Low-Resource Settings Robert Wolfe Isaac Slaughter Bin Han Bingbing Wen Yiwei Yang ... Bernease Herman E. Brown Zening Qu Nicholas Weber Bill Howe 40 4 0 27 May 2024
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition C. Lebeda Matthew Regehr Gautam Kamath Thomas Steinke 53 9 0 27 May 2024
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model Tudor Cebere A. Bellet Nicolas Papernot 30 9 0 23 May 2024
Federated Domain-Specific Knowledge Transfer on Large Language Models Using Synthetic Data Haoran Li Xinyuan Zhao Dadi Guo Hanlin Gu Ziqian Zeng Yuxing Han Yangqiu Song Lixin Fan Qiang Yang 23 1 0 23 May 2024
Nearly Tight Black-Box Auditing of Differentially Private Machine Learning Meenatchi Sundaram Muthu Selva Annamalai Emiliano De Cristofaro 44 11 0 23 May 2024
Navigating Heterogeneity and Privacy in One-Shot Federated Learning with Diffusion Models Matías Mendieta Guangyu Sun Cheng Chen 23 5 0 02 May 2024
Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data Vikhyat Agrawal S. Kalmady Venkataseetharam Manoj Malipeddi Manisimha Manthena Weijie Sun Saiful Islam Abram Hindle Padma Kaul Russell Greiner FedML 23 5 0 26 Apr 2024
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models Juntaek Lim Youngeun Kwon Ranggi Hwang Kiwan Maeng Edward Suh Minsoo Rhu SyDa 31 0 0 12 Apr 2024
pfl-research: simulation framework for accelerating research in Private Federated Learning Filip Granqvist Congzheng Song Áine Cahill Rogier van Dalen Martin Pelikan Yi Sheng Chan Xiaojun Feng Natarajan Krishnaswami Vojta Jina Mona Chitnis FedML 39 6 0 09 Apr 2024
Privacy Backdoors: Stealing Data with Corrupted Pretrained Models Shanglun Feng Florian Tramèr SILM 38 14 0 30 Mar 2024
How Private are DP-SGD Implementations? Lynn Chua Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 43 12 0 26 Mar 2024
TablePuppet: A Generic Framework for Relational Federated Learning Lijie Xu Chulin Xie Yiran Guo Gustavo Alonso Bo-wen Li Guoliang Li Wei Wang Wentao Wu Ce Zhang FedML 36 0 0 23 Mar 2024
Differentially Private Next-Token Prediction of Large Language Models James Flemings Meisam Razaviyayn Murali Annavaram 28 6 0 22 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 31 4 0 21 Mar 2024
Improving LoRA in Privacy-preserving Federated Learning Youbang Sun Zitao Li Yaliang Li Bolin Ding 29 57 0 18 Mar 2024
Sentinel-Guided Zero-Shot Learning: A Collaborative Paradigm without Real Data Exposure Fan Wan Xingyu Miao Haoran Duan Jingjing Deng Rui Gao Yang Long VLM 39 4 0 14 Mar 2024
Quantifying and Mitigating Privacy Risks for Tabular Generative Models Chaoyi Zhu Jiayi Tang Hans Brouwer Juan F. Pérez Marten van Dijk Lydia Y. Chen 60 5 0 12 Mar 2024
Inverse-Free Fast Natural Gradient Descent Method for Deep Learning Xinwei Ou Ce Zhu Xiaolin Huang Yipeng Liu ODL 42 0 0 06 Mar 2024
Differentially Private Representation Learning via Image Captioning Tom Sander Yaodong Yu Maziar Sanjabi Alain Durmus Yi Ma Kamalika Chaudhuri Chuan Guo 71 3 0 04 Mar 2024
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach Qi Tan Qi Li Yi Zhao Zhuotao Liu Xiaobing Guo Ke Xu FedML 39 2 0 02 Mar 2024
Differentially Private Knowledge Distillation via Synthetic Text Generation James Flemings Murali Annavaram SyDa 42 11 0 01 Mar 2024
On the Convergence of Differentially-Private Fine-tuning: To Linearly Probe or to Fully Fine-tune? Shuqi Ke Charlie Hou Giulia Fanti Sewoong Oh 38 4 0 29 Feb 2024
Pre-training Differentially Private Models with Limited Public Data Zhiqi Bu Xinwei Zhang Mingyi Hong Sheng Zha George Karypis 79 3 0 28 Feb 2024
Unveiling Privacy, Memorization, and Input Curvature Links Deepak Ravikumar Efstathia Soufleri Abolfazl Hashemi Kaushik Roy 54 5 0 28 Feb 2024
Differentially Private Fair Binary Classifications Hrad Ghoukasian S. Asoodeh FaML 34 1 0 23 Feb 2024
Closed-Form Bounds for DP-SGD against Record-level Inference Giovanni Cherubin Boris Köpf Andrew J. Paverd Shruti Tople Lukas Wutschitz Santiago Zanella Béguelin 38 2 0 22 Feb 2024
PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining Mishaal Kazmi H. Lautraite Alireza Akbari Mauricio Soroco Qiaoyue Tang Tao Wang Sébastien Gambs Mathias Lécuyer 37 8 0 12 Feb 2024
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off Yuecheng Li Lele Fu Tong Wang Jian Lou Bin Chen Lei Yang Zibin Zheng Zibin Zheng Chuan Chen FedML 70 4 0 10 Feb 2024
Privacy Profiles for Private Selection Antti Koskela Rachel Redberg Yu-Xiang Wang 32 1 0 09 Feb 2024
De-amplifying Bias from Differential Privacy in Language Model Fine-tuning Sanjari Srivastava Piotr (Peter) Mardziel Zhikhun Zhang Archana Ahlawat Anupam Datta John C. Mitchell 37 1 0 07 Feb 2024
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation Ossi Raisa Joonas Jälkö Antti Honkela 30 6 0 06 Feb 2024
Decentralised, Collaborative, and Privacy-preserving Machine Learning for Multi-Hospital Data Cong Fang Adam Dziedzic Lin Zhang Laura Oliva A. Verma Fahad Razak Nicolas Papernot Bo Wang OOD 17 11 0 31 Jan 2024
Cross-silo Federated Learning with Record-level Personalized Differential Privacy Junxu Liu Jian Lou Li Xiong Jinfei Liu Xiaofeng Meng 28 5 0 29 Jan 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
Facebook Report on Privacy of fNIRS data Md. Imran Hossen Sai Venkatesh Chilukoti Liqun Shan Vijay Srinivas Tida X. Hei 25 0 0 01 Jan 2024
AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning Hideaki Takahashi SILM 30 2 0 29 Dec 2023
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift Pratiksha Thaker Amrith Rajagopal Setlur Zhiwei Steven Wu Virginia Smith 39 2 0 24 Dec 2023
An Empirical Study of Efficiency and Privacy of Federated Learning Algorithms Sofia Zahri Hajar Bennouri A. Abdelmoniem FedML 11 1 0 24 Dec 2023
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction) Qiaoyue Tang Frederick Shpilevskiy Mathias Lécuyer 40 14 0 21 Dec 2023
Federated learning with differential privacy and an untrusted aggregator Kunlong Liu Trinabh Gupta 42 0 0 17 Dec 2023
FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed Settings Jean Ogier du Terrail Quentin Klopfenstein Honghao Li Imke Mayer Nicolas Loiseau Mohammad Hallal Félix Balazard M. Andreux 18 2 0 28 Nov 2023
Automated discovery of trade-off between utility, privacy and fairness in machine learning models Bogdan Ficiu Neil D. Lawrence Andrei Paleyes 29 1 0 27 Nov 2023
DP-NMT: Scalable Differentially-Private Machine Translation Timour Igamberdiev Doan Nam Long Vu Felix Künnecke Zhuo Yu Jannik Holmer Ivan Habernal 31 7 0 24 Nov 2023
Zero redundancy distributed learning with differential privacy Zhiqi Bu Justin Chiu Ruixuan Liu Sheng Zha George Karypis 45 8 0 20 Nov 2023
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent Lauren Watson Eric Gan Mohan Dantam Baharan Mirzasoleiman Rik Sarkar 23 1 0 12 Nov 2023
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$ -Differential Privacy Chendi Wang Buxin Su Jiayuan Ye Reza Shokri Weijie J. Su FedML 18 10 0 30 Oct 2023
On the accuracy and efficiency of group-wise clipping in differentially private optimization Zhiqi Bu Ruixuan Liu Yu-Xiang Wang Sheng Zha George Karypis VLM 32 4 0 30 Oct 2023
DP-SGD with weight clipping Antoine Barczewski Jan Ramon 11 1 0 27 Oct 2023