Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 1,225 papers shown

Title
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 50 16 0 20 Sep 2021
Releasing Graph Neural Networks with Differential Privacy Guarantees Iyiola E. Olatunji Thorben Funke Megha Khosla 54 46 0 18 Sep 2021
Enforcing fairness in private federated learning via the modified method of differential multipliers Borja Rodríguez Gálvez Filip Granqvist Rogier van Dalen M. Seigel FedML 48 53 0 17 Sep 2021
Private Multi-Task Learning: Formulation and Applications to Federated Learning Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 39 19 0 30 Aug 2021
Selective Differential Privacy for Language Modeling Weiyan Shi Aiqi Cui Evan Li R. Jia Zhou Yu 30 68 0 30 Aug 2021
EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning Hongbin Liu Jinyuan Jia Wenjie Qu Neil Zhenqiang Gong 13 94 0 25 Aug 2021
Federated Learning for Open Banking Guodong Long Yue Tan Jing Jiang Chengqi Zhang AIFin FedML 51 279 0 24 Aug 2021
Data-Free Evaluation of User Contributions in Federated Learning Hongtao Lv Zhenzhe Zheng Tie-Mei Luo Fan Wu Shaojie Tang Lifeng Hua Rongfei Jia Chengfei Lv FedML 23 23 0 24 Aug 2021
Federated Learning Meets Fairness and Differential Privacy P. Manisha Sankarshan Damle Sujit Gujar FedML 43 21 0 23 Aug 2021
Order Optimal Bounds for One-Shot Federated Learning over non-Convex Loss Functions Arsalan Sharifnassab Saber Salehkaleybar S. J. Golestani FedML 13 0 0 19 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 37 101 0 10 Aug 2021
Efficient Hyperparameter Optimization for Differentially Private Deep Learning Aman Priyanshu Rakshit Naidu Fatemehsadat Mireshghallah Mohammad Malekzadeh 44 5 0 09 Aug 2021
Large-Scale Differentially Private BERT Rohan Anil Badih Ghazi Vineet Gupta Ravi Kumar Pasin Manurangsi 41 132 0 03 Aug 2021
Private Retrieval, Computing and Learning: Recent Progress and Future Challenges S. Ulukus Salman Avestimehr Michael C. Gastpar S. Jafar Ravi Tandon Chao Tian FedML 52 66 0 30 Jul 2021
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data Lijie Hu Shuo Ni Hanshen Xiao Di Wang 46 52 0 23 Jul 2021
Generative adversarial networks in time series: A survey and taxonomy Eoin Brophy Zhengwei Wang Qi She Tomas E. Ward EGVM AI4TS 30 57 0 23 Jul 2021
Defending against Reconstruction Attack in Vertical Federated Learning Jiankai Sun Yuanshun Yao Weihao Gao Junyuan Xie Chong-Jun Wang AAML FedML 29 28 0 21 Jul 2021
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates Steve Chien Prateek Jain Walid Krichene Steffen Rendle Shuang Song Abhradeep Thakurta Li Zhang 30 19 0 20 Jul 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 191 413 0 14 Jul 2021
An Efficient DP-SGD Mechanism for Large Scale NLP Models Christophe Dupuy Radhika Arava Rahul Gupta Anna Rumshisky SyDa 31 35 0 14 Jul 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 198 0 12 Jul 2021
Challenges for machine learning in clinical translation of big data imaging studies Nicola K. Dinsdale Emma Bluemke V. Sundaresan M. Jenkinson Stephen Smith Ana I. L. Namburete AI4CE 50 42 0 07 Jul 2021
DTGAN: Differential Private Training for Tabular GANs A. Kunar Robert Birke Zilong Zhao L. Chen 30 11 0 06 Jul 2021
SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging Miao Zhang Liangqiong Qu Praveer Singh Jayashree Kalpathy-Cramer D. Rubin OOD FedML 34 62 0 06 Jul 2021
Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 33 71 0 04 Jul 2021
Smoothed Differential Privacy Ao Liu Yu-Xiang Wang Lirong Xia 55 0 0 04 Jul 2021
Gradient-Leakage Resilient Federated Learning Wenqi Wei Ling Liu Yanzhao Wu Gong Su Arun Iyengar FedML 24 81 0 02 Jul 2021
Benchmarking Differential Privacy and Federated Learning for BERT Models Priya Basu Tiasa Singha Roy Rakshit Naidu Zumrut Muftuoglu Sahib Singh Fatemehsadat Mireshghallah FedML AI4MH 29 50 0 26 Jun 2021
Private Adaptive Gradient Methods for Convex Optimization Hilal Asi John C. Duchi Alireza Fallah O. Javidbakht Kunal Talwar 41 53 0 25 Jun 2021
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy Xinwei Zhang Xiangyi Chen Min-Fong Hong Zhiwei Steven Wu Jinfeng Yi FedML 37 91 0 25 Jun 2021
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data Paul Pu Liang Terrance Liu Anna Cai Michal Muszynski Ryo Ishii Nicholas B. Allen Randy P. Auerbach David Brent Ruslan Salakhutdinov Louis-Philippe Morency 55 16 0 24 Jun 2021
When Differential Privacy Meets Interpretability: A Case Study Rakshit Naidu Aman Priyanshu Aadith Kumar Sasikanth Kotti Haofan Wang Fatemehsadat Mireshghallah 32 9 0 24 Jun 2021
Membership Inference on Word Embedding and Beyond Saeed Mahloujifar Huseyin A. Inan Melissa Chase Esha Ghosh Marcello Hasegawa MIACV SILM 30 46 0 21 Jun 2021
Adversarial Examples Make Strong Poisons Liam H. Fowl Micah Goldblum Ping Yeh-Chiang Jonas Geiping Wojtek Czaja Tom Goldstein SILM 42 134 0 21 Jun 2021
Low-Latency Federated Learning over Wireless Channels with Differential Privacy Kang Wei Jun Li Chuan Ma Ming Ding Cailian Chen Shi Jin Zhu Han H. Vincent Poor FedML 40 73 0 20 Jun 2021
A Survey of Privacy Vulnerabilities of Mobile Device Sensors Paula Delgado-Santos Giuseppe Stragapede Ruben Tolosana R. Guest F. Deravi R. Vera-Rodríguez PILM 37 46 0 18 Jun 2021
Large Scale Private Learning via Low-rank Reparametrization Da Yu Huishuai Zhang Wei Chen Jian Yin Tie-Yan Liu 34 101 0 17 Jun 2021
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch Hossein Souri Liam H. Fowl Ramalingam Chellappa Micah Goldblum Tom Goldstein SILM 36 125 0 16 Jun 2021
Optimal Accounting of Differential Privacy via Characteristic Function Yuqing Zhu Jinshuo Dong Yu Wang 29 99 0 16 Jun 2021
A Survey on Fault-tolerance in Distributed Optimization and Machine Learning Shuo Liu AI4CE OOD 58 13 0 16 Jun 2021
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks Chulin Xie Minghao Chen Pin-Yu Chen Yue Liu FedML 41 165 0 15 Jun 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 23 113 0 15 Jun 2021
Federated Learning with Buffered Asynchronous Aggregation John Nguyen Kshitiz Malik Hongyuan Zhan Ashkan Yousefpour Michael G. Rabbat Mani Malek Dzmitry Huba FedML 43 292 0 11 Jun 2021
Differentially Private Federated Learning via Inexact ADMM Minseok Ryu Kibaek Kim FedML 44 15 0 11 Jun 2021
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning Jinhyun So Ramy E. Ali Başak Güler Jiantao Jiao Salman Avestimehr FedML 50 78 0 07 Jun 2021
GraphMI: Extracting Private Graph Data from Graph Neural Networks Zaixi Zhang Qi Liu Zhenya Huang Hao Wang Chengqiang Lu Chuanren Liu Enhong Chen 31 68 0 05 Jun 2021
Federated Neural Collaborative Filtering V. Perifanis P. Efraimidis FedML 26 92 0 02 Jun 2021
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning He Yang 22 27 0 01 Jun 2021
Privately Learning Subspaces Vikrant Singhal Thomas Steinke 32 20 0 28 May 2021
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs Mohammad Malekzadeh Anastasia Borovykh Deniz Gündüz MIACV 36 42 0 25 May 2021