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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
Key Protected Classification for Collaborative Learning Mert Bulent Sariyildiz R. G. Cinbis Erman Ayday 49 10 0 27 Aug 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 179 4,584 0 21 Aug 2019
That which we call private Ulfar Erlingsson Ilya Mironov A. Raghunathan Shuang Song 73 26 0 08 Aug 2019
Local Differential Privacy for Deep Learning Pathum Chamikara Mahawaga Arachchige P. Bertók I. Khalil Dongxi Liu S. Çamtepe Mohammed Atiquzzaman 110 225 0 08 Aug 2019
Privately Answering Classification Queries in the Agnostic PAC Model Anupama Nandi Raef Bassily 107 26 0 31 Jul 2019
A Federated Learning Approach for Mobile Packet Classification Evita Bakopoulou Bálint Tillman A. Markopoulou 62 30 0 30 Jul 2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection Yue Liu Zeyi Wen Zhaomin Wu Sixu Hu Naibo Wang Yuan N. Li Xu Liu Bingsheng He FedML 130 1,015 0 23 Jul 2019
Neural Epitome Search for Architecture-Agnostic Network Compression Daquan Zhou Xiaojie Jin Qibin Hou Kaixin Wang Jianchao Yang Jiashi Feng 91 13 0 12 Jul 2019
Making AI Forget You: Data Deletion in Machine Learning Antonio A. Ginart M. Guan Gregory Valiant James Zou MU 112 481 0 11 Jul 2019
On the Privacy Risks of Model Explanations Reza Shokri Martin Strobel Yair Zick MIACV PILM SILM FAtt 129 38 0 29 Jun 2019
DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM Bao Wang Quanquan Gu M. Boedihardjo Farzin Barekat Stanley J. Osher 129 25 0 28 Jun 2019
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks Tribhuvanesh Orekondy Bernt Schiele Mario Fritz AAML 83 167 0 26 Jun 2019
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators Yunhui Long Wei Ping Zhuolin Yang B. Kailkhura Aston Zhang C.A. Gunter Yue Liu 122 74 0 21 Jun 2019
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation Han Zhao Jianfeng Chi Yuan Tian Geoffrey J. Gordon MIACV 51 2 0 19 Jun 2019
Membership Privacy for Machine Learning Models Through Knowledge Transfer Virat Shejwalkar Amir Houmansadr 88 10 0 15 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 204 504 0 12 Jun 2019
Interpretable and Differentially Private Predictions Frederik Harder Matthias Bauer Mijung Park FAtt 74 53 0 05 Jun 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 163 126 0 04 Jun 2019
Towards Fair and Privacy-Preserving Federated Deep Models Lingjuan Lyu Jiangshan Yu Karthik Nandakumar Yitong Li Xingjun Ma Jiong Jin Han Yu Kee Siong Ng FedML 43 20 0 04 Jun 2019
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification Bingzhe Wu Shiwan Zhao Guangyu Sun Xiaolu Zhang Zhong Su C. Zeng Zhihong Liu 73 41 0 30 May 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 108 344 0 09 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot Nicholas Carlini Ian Goodfellow Nicolas Papernot Avital Oliver Colin Raffel 235 3,051 0 06 May 2019
Mimic Learning to Generate a Shareable Network Intrusion Detection Model Ahmed A. Shafee Mohamed Baza Douglas A. Talbert M. Fouda Mahmoud Nabil Mohamed Mahmoud 77 29 0 02 May 2019
Privacy-preserving Active Learning on Sensitive Data for User Intent Classification Oluwaseyi Feyisetan Thomas Drake Borja Balle Tom Diethe 52 11 0 26 Mar 2019
One-Shot Federated Learning Neel Guha Ameet Talwalkar Virginia Smith FedML 67 219 0 28 Feb 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David Evans 147 7 0 24 Feb 2019
Differentially Private Continual Learning Sebastian Farquhar Y. Gal FedML MU 50 12 0 18 Feb 2019
Privacy Preserving Off-Policy Evaluation Tengyang Xie Philip S. Thomas G. Miklau OffRL 46 4 0 01 Feb 2019
Representation Transfer for Differentially Private Drug Sensitivity Prediction Teppo Niinimaki Mikko A. Heikkilä Antti Honkela Samuel Kaski OOD 16 8 0 29 Jan 2019
Bayesian Differential Privacy for Machine Learning Aleksei Triastcyn Boi Faltings 78 2 0 28 Jan 2019
Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data Lorenzo Frigerio Anderson Santana de Oliveira L. Gomez Patrick Duverger SyDa AI4TS 90 109 0 08 Jan 2019
Application-driven Privacy-preserving Data Publishing with Correlated Attributes A. Rezaei Chaowei Xiao Jie Gao Yue Liu Sirajum Munir 48 14 0 26 Dec 2018
A General Approach to Adding Differential Privacy to Iterative Training Procedures H. B. McMahan Galen Andrew Ulfar Erlingsson Steve Chien Ilya Mironov Nicolas Papernot Peter Kairouz 104 193 0 15 Dec 2018
No Peek: A Survey of private distributed deep learning Praneeth Vepakomma Tristan Swedish Ramesh Raskar O. Gupta Abhimanyu Dubey SyDa FedML 83 100 0 08 Dec 2018
MEAL: Multi-Model Ensemble via Adversarial Learning Zhiqiang Shen Zhankui He Xiangyang Xue AAML FedML 88 147 0 06 Dec 2018
Differentially Private Data Generative Models Qingrong Chen Chong Xiang Minhui Xue Yue Liu Nikita Borisov Dali Kaafar Haojin Zhu SyDa AAML 80 79 0 06 Dec 2018
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 125 713 0 03 Dec 2018
The Power of The Hybrid Model for Mean Estimation Brendan Avent Yatharth Dubey Aleksandra Korolova 98 17 0 29 Nov 2018
An overview of deep learning in medical imaging focusing on MRI A. Lundervold A. Lundervold OOD 112 1,655 0 25 Nov 2018
Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference Edward Chou Josh Beal Daniel Levy Serena Yeung Albert Haque Li Fei-Fei 67 200 0 25 Nov 2018
Differential Private Stack Generalization with an Application to Diabetes Prediction Quanming Yao Xiawei Guo James T. Kwok Wei-Wei Tu Yuqiang Chen Wenyuan Dai Qiang Yang 28 19 0 23 Nov 2018
Private Selection from Private Candidates Jingcheng Liu Kunal Talwar 74 134 0 19 Nov 2018
How to Use Heuristics for Differential Privacy Seth Neel Aaron Roth Zhiwei Steven Wu 76 26 0 19 Nov 2018
Private Model Compression via Knowledge Distillation Ji Wang Weidong Bao Lichao Sun Xiaomin Zhu Bokai Cao Philip S. Yu FedML 78 120 0 13 Nov 2018
A generic framework for privacy preserving deep learning Wenbo Guo Yunzhe Tao Morten Dahl Sui Huang Masashi Sugiyama Daniel Rueckert Lin Lin FedML 115 438 0 09 Nov 2018
Private Machine Learning in TensorFlow using Secure Computation Morten Dahl Jason V. Mancuso Yann Dupis Ben Decoste Morgan Giraud Ian Livingstone Justin Patriquin Gavin Uhma FedML 72 78 0 18 Oct 2018
Deep Reinforcement Learning Yuxi Li VLM OffRL 194 144 0 15 Oct 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 144 613 0 14 Oct 2018
Privado: Practical and Secure DNN Inference with Enclaves Karan Grover Shruti Tople Shweta Shinde Ranjita Bhagwan Ramachandran Ramjee FedML SILM 72 46 0 01 Oct 2018
Deep Learning Towards Mobile Applications Ji Wang Bokai Cao Philip S. Yu Lichao Sun Weidong Bao Xiaomin Zhu HAI 87 99 0 10 Sep 2018