Deep Learning with Label Differential Privacy

11 February 2021

Papers citing "Deep Learning with Label Differential Privacy"

50 / 100 papers shown

Title
Multi-class Item Mining under Local Differential Privacy Yulian Mao Qingqing Ye Rong Du Qi Wang Kai Huang Haibo Hu 17 0 0 18 Apr 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 41 0 0 17 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 44 0 0 04 Mar 2025
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification Anan Kabaha Dana Drachsler-Cohen AAML 43 0 0 23 Feb 2025
Towards User-level Private Reinforcement Learning with Human Feedback J. Zhang Mingxi Lei Meng Ding Mengdi Li Zihang Xiang Difei Xu Jinhui Xu Di Wang 39 0 0 22 Feb 2025
Learning with Noisy Labels: the Exploration of Error Bounds in Classification Haixia Liu Boxiao Li Can Yang Yang Wang 31 0 0 28 Jan 2025
Estimating the Conformal Prediction Threshold from Noisy Labels Coby Penso Jacob Goldberger Ethan Fetaya 36 1 0 22 Jan 2025
Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Andrei Semenov Philip Zmushko Alexander Pichugin Aleksandr Beznosikov 74 0 0 16 Dec 2024
Aggregating Data for Optimal and Private Learning Sushant Agarwal Yukti Makhija Rishi Saket A. Raghuveer FedML 66 0 0 28 Nov 2024
Inference Privacy: Properties and Mechanisms Fengwei Tian Ravi Tandon 64 0 0 27 Nov 2024
Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy Maryam Aliakbarpour Syomantak Chaudhuri T. Courtade Alireza Fallah Michael I. Jordan 16 0 0 24 Oct 2024
ParallelSFL: A Novel Split Federated Learning Framework Tackling Heterogeneity Issues Yunming Liao Yang Xu Hongli Xu Zhiwei Yao Liusheng Huang C. Qiao FedML 24 5 0 02 Oct 2024
Privacy-Preserving Student Learning with Differentially Private Data-Free Distillation Bochao Liu Jianghu Lu Pengju Wang Junjie Zhang Dan Zeng Zhenxing Qian Shiming Ge 11 1 0 19 Sep 2024
$S^2$ NeRF: Privacy-preserving Training Framework for NeRF Bokang Zhang Yanglin Zhang Zhikun Zhang Jinglan Yang Lingying Huang Junfeng Wu 30 2 0 03 Sep 2024
A Differentially Private Blockchain-Based Approach for Vertical Federated Learning Linh Tran Sanjay Chari Md. Saikat Islam Khan Aaron Zachariah Stacy Patterson O. Seneviratne FedML 22 2 0 09 Jul 2024
On Convex Optimization with Semi-Sensitive Features Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Raghu Meka Chiyuan Zhang 19 0 0 27 Jun 2024
Order-Optimal Instance-Dependent Bounds for Offline Reinforcement Learning with Preference Feedback Zhirui Chen Vincent Y. F. Tan OffRL 31 0 0 18 Jun 2024
Retraining with Predicted Hard Labels Provably Increases Model Accuracy Rudrajit Das Inderjit S Dhillon Alessandro Epasto Adel Javanmard Jieming Mao Vahab Mirrokni Sujay Sanghavi Peilin Zhong 32 1 0 17 Jun 2024
Rethinking the impact of noisy labels in graph classification: A utility and privacy perspective De Li Xianxian Li Zeming Gan Qiyu Li Bin Qu Jinyan Wang NoLa 38 1 0 11 Jun 2024
Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation Honglei Zhang Haoxuan Li Jundong Chen Sen Cui Kunda Yan Abudukelimu Wuerkaixi Xin Zhou Zhiqi Shen Yidong Li FedML 16 4 0 06 Jun 2024
Auditing Privacy Mechanisms via Label Inference Attacks R. Busa-Fekete Travis Dick Claudio Gentile Andrés Munoz Medina Adam D. Smith Marika Swanberg 16 0 0 04 Jun 2024
FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation Hanlin Gu Jiahuan Luo Yan Kang Yuan Yao Gongxi Zhu Bowen Li Jie Li Lixin Fan Qiang Yang 37 0 0 03 Jun 2024
LabObf: A Label Protection Scheme for Vertical Federated Learning Through Label Obfuscation Ying He Mingyang Niu Jingyu Hua Yunlong Mao Xu Huang Chen Li Sheng Zhong FedML 35 0 0 27 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 18 4 0 27 May 2024
Enhancing Learning with Label Differential Privacy by Vector Approximation Puning Zhao Rongfei Fan Huiwen Wu Qingming Li Jiafei Wu Zhe Liu 16 1 0 24 May 2024
Locally Private Estimation with Public Features Yuheng Ma Ke Jia Hanfang Yang 34 3 0 22 May 2024
Locally Differentially Private In-Context Learning Chunyan Zheng Keke Sun Wenhao Zhao Haibo Zhou Lixin Jiang Shaoyang Song Chunlai Zhou 22 2 0 07 May 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 21 0 0 23 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 XiaoFeng Wang AAML 38 6 0 05 Mar 2024
A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective Lei Yu Meng Han Yiming Li Changting Lin Yao Zhang ... Yan Liu Haiqin Weng Yuseok Jeon Ka-Ho Chow Stacy Patterson FedML 58 9 0 06 Feb 2024
Online Distribution Learning with Local Private Constraints Jin Sima Changlong Wu O. Milenkovic Wojtek Szpankowski 14 0 0 01 Feb 2024
Training Differentially Private Ad Prediction Models with Semi-Sensitive Features Lynn Chua Qiliang Cui Badih Ghazi Charlie Harrison Pritish Kamath ... Pasin Manurangsi Krishnagiri Narra Amer Sinha A. Varadarajan Chiyuan Zhang AAML 20 5 0 26 Jan 2024
Classification with Partially Private Features Zeyu Shen A. Krishnaswamy Janardhan Kulkarni Kamesh Munagala 26 4 0 11 Dec 2023
Optimal Unbiased Randomizers for Regression with Label Differential Privacy Ashwinkumar Badanidiyuru Badih Ghazi Pritish Kamath Ravi Kumar Ethan Leeman Pasin Manurangsi A. Varadarajan Chiyuan Zhang 15 4 0 09 Dec 2023
MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulation Yunming Liao Yang Xu Hong-Ze Xu Lun Wang Zhiwei Yao C. Qiao FedML MoMe 17 10 0 22 Nov 2023
Does Differential Privacy Prevent Backdoor Attacks in Practice? Fereshteh Razmi Jian Lou Li Xiong AAML 17 0 0 10 Nov 2023
Differentially Private Reward Estimation with Preference Feedback Sayak Ray Chowdhury Xingyu Zhou Nagarajan Natarajan 26 4 0 30 Oct 2023
Private Learning with Public Features Walid Krichene Nicolas Mayoraz Steffen Rendle Shuang Song Abhradeep Thakurta Li Zhang 13 6 0 24 Oct 2023
Label Differential Privacy via Aggregation Anand Brahmbhatt Rishi Saket Shreyas Havaldar Anshul Nasery A. Raghuveer 27 0 0 16 Oct 2023
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning Tianyuan Zou Zixuan Gu Yuanqin He Hideaki Takahashi Yang Janet Liu Ya-Qin Zhang FedML 25 5 0 15 Oct 2023
Little is Enough: Improving Privacy by Sharing Labels in Federated Semi-Supervised Learning Amr Abourayya Jens Kleesiek Kanishka Rao Erman Ayday Bharat Rao Geoff Webb Michael Kamp FedML 29 0 0 09 Oct 2023
A Survey of Data Security: Practices from Cybersecurity and Challenges of Machine Learning Padmaksha Roy Jaganmohan Chandrasekaran Erin Lanus Laura J. Freeman Jeremy Werner 12 3 0 06 Oct 2023
DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass Minxin Du Xiang Yue Sherman S. M. Chow Tianhao Wang Chenyu Huang Huan Sun SILM 15 58 0 13 Sep 2023
Optimizing Hierarchical Queries for the Attribution Reporting API Matthew Dawson Badih Ghazi Pritish Kamath Kapil Kumar Ravi Kumar ... Pasin Manurangsi Nishanth Mundru Harikesh S. Nair Adam Sealfon Shengyu Zhu 8 4 0 25 Aug 2023
Defending Label Inference Attacks in Split Learning under Regression Setting Haoze Qiu Fei Zheng Chaochao Chen Xiaolin Zheng FedML AAML 14 2 0 18 Aug 2023
Label Inference Attacks against Node-level Vertical Federated GNNs Marco Arazzi Mauro Conti Stefanos Koffas Marina Krček Antonino Nocera S. Picek Jing Xu FedML AAML 11 1 0 04 Aug 2023
Causal Inference with Differentially Private (Clustered) Outcomes Adel Javanmard Vahab Mirrokni Jean Pouget-Abadie 17 2 0 02 Aug 2023
Eliminating Label Leakage in Tree-Based Vertical Federated Learning Hideaki Takahashi J. Liu Yang Liu AAML FedML 17 5 0 19 Jul 2023
Differentially Private Video Activity Recognition Zelun Luo Yuliang Zou Yijin Yang Zane Durante De-An Huang Zhiding Yu Chaowei Xiao L. Fei-Fei Anima Anandkumar PICV 17 3 0 27 Jun 2023
Quantifying Overfitting: Evaluating Neural Network Performance through Analysis of Null Space Hossein Rezaei Mohammad Sabokrou 12 3 0 30 May 2023