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Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

18 October 2016

Papers citing "Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data"

50 / 353 papers shown

Title
On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation Yucong Liu ChiHua Wang Guang Cheng 119 8 0 28 Nov 2022
Private Multi-Winner Voting for Machine Learning Adam Dziedzic Christopher A. Choquette-Choo Natalie Dullerud Vinith Suriyakumar Ali Shahin Shamsabadi Muhammad Ahmad Kaleem S. Jha Nicolas Papernot Xiao Wang 104 1 0 23 Nov 2022
Private Ad Modeling with DP-SGD Carson E. Denison Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Krishnagiri Narra Amer Sinha A. Varadarajan Chiyuan Zhang 86 14 0 21 Nov 2022
DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder Bjarne Pfitzner B. Arnrich FedML 84 18 0 21 Nov 2022
Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version) Lucas Lange Maja Schneider Peter Christen Erhard Rahm 93 7 0 21 Nov 2022
A Survey on Differential Privacy with Machine Learning and Future Outlook Samah Baraheem Z. Yao SyDa 68 1 0 19 Nov 2022
Knowledge Distillation for Federated Learning: a Practical Guide Alessio Mora Irene Tenison Paolo Bellavista Irina Rish FedML 66 31 0 09 Nov 2022
Private Set Generation with Discriminative Information Dingfan Chen Raouf Kerkouche Mario Fritz DD 80 39 0 07 Nov 2022
Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels Qiuchen Zhang Jing Ma Jian Lou Li Xiong Xiaoqian Jiang NoLa 62 0 0 03 Nov 2022
Teacher-Student Architecture for Knowledge Learning: A Survey Chengming Hu Xuan Li Dan Liu Xi Chen Ju Wang Xue Liu 104 35 0 28 Oct 2022
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling Junyuan Hong Lingjuan Lyu Jiayu Zhou Michael Spranger SyDa 99 6 0 23 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Yifan Yang 90 21 0 18 Oct 2022
Federated Learning with Privacy-Preserving Ensemble Attention Distillation Xuan Gong Liangchen Song Rishi Vedula Abhishek Sharma Meng Zheng ... Arun Innanje Terrence Chen Junsong Yuan David Doermann Ziyan Wu FedML 87 28 0 16 Oct 2022
Mitigating Unintended Memorization in Language Models via Alternating Teaching Zhe Liu Xuedong Zhang Fuchun Peng 70 3 0 13 Oct 2022
An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition Chao-Han Huck Yang Jun Qi Sabato Marco Siniscalchi Chin-Hui Lee 86 4 0 12 Oct 2022
Synthetic Dataset Generation for Privacy-Preserving Machine Learning Efstathia Soufleri Gobinda Saha Kaushik Roy DD 135 3 0 06 Oct 2022
In Differential Privacy, There is Truth: On Vote Leakage in Ensemble Private Learning Jiaqi Wang R. Schuster Ilia Shumailov David Lie Nicolas Papernot FedML 79 3 0 22 Sep 2022
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation Xuan Gong Abhishek Sharma Srikrishna Karanam Ziyan Wu Terrence Chen David Doermann Arun Innanje FedML 85 79 0 10 Sep 2022
Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis Shigehiko Schamoni Michael Hagmann Stefan Riezler FedML 58 4 0 01 Sep 2022
Membership Inference Attacks by Exploiting Loss Trajectory Yiyong Liu Zhengyu Zhao Michael Backes Yang Zhang 99 111 0 31 Aug 2022
Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits Marco Schreyer Timur Sattarov Damian Borth MLAU 79 16 0 26 Aug 2022
DiVa: An Accelerator for Differentially Private Machine Learning Beom-Joo Park Ranggi Hwang Dongho Yoon Yoonhyuk Choi Minsoo Rhu 60 9 0 26 Aug 2022
Semi-Supervised and Unsupervised Deep Visual Learning: A Survey Yanbei Chen Massimiliano Mancini Xiatian Zhu Zeynep Akata 157 121 0 24 Aug 2022
"Am I Private and If So, how Many?" - Communicating Privacy Guarantees of Differential Privacy with Risk Communication Formats Daniel Franzen Saskia Nuñez von Voigt Peter Sorries Florian Tschorsch Claudia Muller-Birn 84 21 0 23 Aug 2022
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy Wenqiang Ruan Ming Xu Wenjing Fang Li Wang Lei Wang Wei Han 83 14 0 18 Aug 2022
Private Estimation with Public Data Alex Bie Gautam Kamath Vikrant Singhal 78 31 0 16 Aug 2022
DP $^2$ -VAE: Differentially Private Pre-trained Variational Autoencoders Dihong Jiang Guojun Zhang Mahdi Karami Xi Chen Yunfeng Shao Yaoliang Yu 94 14 0 05 Aug 2022
Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer Jicheng Li Anjana Bhat R. Barmaki ViT 80 5 0 01 Aug 2022
Privacy-Preserving Federated Recurrent Neural Networks Sinem Sav Abdulrahman Diaa Apostolos Pyrgelis Jean-Philippe Bossuat Jean-Pierre Hubaux FedML 101 8 0 28 Jul 2022
Fine-grained Private Knowledge Distillation Yuntong Li Shaowei Wang Yingying Wang Jin Li Yuqiu Qian Bangzhou Xin Wei Yang 94 0 0 27 Jul 2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning Yuanhao Xiong Ruochen Wang Minhao Cheng Felix X. Yu Cho-Jui Hsieh FedML DD 81 85 0 20 Jul 2022
RelaxLoss: Defending Membership Inference Attacks without Losing Utility Dingfan Chen Ning Yu Mario Fritz 123 43 0 12 Jul 2022
Measuring Forgetting of Memorized Training Examples Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 158 111 0 30 Jun 2022
Differentially Private Federated Combinatorial Bandits with Constraints Sambhav Solanki Samhita Kanaparthy Sankarshan Damle Sujit Gujar FedML 67 4 0 27 Jun 2022
Bayesian Estimation of Differential Privacy Santiago Zanella Béguelin Lukas Wutschitz Shruti Tople A. Salem Victor Rühle Andrew Paverd Mohammad Naseri Boris Köpf Daniel Jones 95 40 0 10 Jun 2022
A Critical Review on the Use (and Misuse) of Differential Privacy in Machine Learning Alberto Blanco-Justicia David Sánchez J. Domingo-Ferrer K. Muralidhar 74 63 0 09 Jun 2022
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent Da Yu Gautam Kamath Janardhan Kulkarni Tie-Yan Liu Jian Yin Huishuai Zhang 158 22 0 06 Jun 2022
Differentially Private Model Compression Fatemehsadat Mireshghallah A. Backurs Huseyin A. Inan Lukas Wutschitz Janardhan Kulkarni SyDa 57 14 0 03 Jun 2022
FedAUXfdp: Differentially Private One-Shot Federated Distillation Haley Hoech R. Rischke Karsten Müller Wojciech Samek FedML 64 4 0 30 May 2022
Differential Privacy: What is all the noise about? Roxana Dánger Mercaderes 55 3 0 19 May 2022
On the Difficulty of Defending Self-Supervised Learning against Model Extraction Adam Dziedzic Nikita Dhawan Muhammad Ahmad Kaleem Jonas Guan Nicolas Papernot MIACV 115 26 0 16 May 2022
Synthetic Data -- what, why and how? James Jordon Lukasz Szpruch F. Houssiau M. Bottarelli Giovanni Cherubin Carsten Maple Samuel N. Cohen Adrian Weller 96 120 0 06 May 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability Enyan Dai Tianxiang Zhao Huaisheng Zhu Jun Xu Zhimeng Guo Hui Liu Jiliang Tang Suhang Wang 109 144 0 18 Apr 2022
Just Fine-tune Twice: Selective Differential Privacy for Large Language Models Weiyan Shi Ryan Shea Si-An Chen Chiyuan Zhang R. Jia Zhou Yu AAML 97 42 0 15 Apr 2022
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 70 12 0 11 Apr 2022
Supervised Robustness-preserving Data-free Neural Network Pruning Mark Huasong Meng Guangdong Bai Sin Gee Teo Jin Song Dong AAML 96 4 0 02 Apr 2022
CTAB-GAN+: Enhancing Tabular Data Synthesis Zilong Zhao A. Kunar Robert Birke L. Chen 102 86 0 01 Apr 2022
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE Yuqing Zhu Yu Wang 106 18 0 30 Mar 2022
Distributed data analytics Richard Mortier Hamed Haddadi S. S. Rodríguez Liang Wang 72 2 0 26 Mar 2022
Mixed Differential Privacy in Computer Vision Aditya Golatkar Alessandro Achille Yu Wang Aaron Roth Michael Kearns Stefano Soatto PICV VLM 96 50 0 22 Mar 2022