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 / 216 papers shown

Title
Revisiting Hyperparameter Tuning with Differential Privacy Youlong Ding Xueyang Wu 24 0 0 03 Nov 2022
Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels Qiuchen Zhang Jing Ma Jian Lou Li Xiong Xiaoqian Jiang NoLa 21 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 29 35 0 28 Oct 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 22 14 0 27 Oct 2022
Federated Continual Learning to Detect Accounting Anomalies in Financial Auditing Marco Schreyer Hamed Hemati Damian Borth M. Vasarhelyi FedML 45 3 0 26 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Yin Yang 46 20 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 30 27 0 16 Oct 2022
Mitigating Unintended Memorization in Language Models via Alternating Teaching Zhe Liu Xuedong Zhang Fuchun Peng 38 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 26 4 0 12 Oct 2022
An Experimental Study on Private Aggregation of Teacher Ensemble Learning for End-to-End Speech Recognition Chao-Han Huck Yang I-Fan Chen A. Stolcke Sabato Marco Siniscalchi Chin-Hui Lee 32 2 0 11 Oct 2022
Differentially Private Deep Learning with ModelMix Hanshen Xiao Jun Wan S. Devadas 29 3 0 07 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 33 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 24 70 0 10 Sep 2022
Membership Inference Attacks by Exploiting Loss Trajectory Yiyong Liu Zhengyu Zhao Michael Backes Yang Zhang 27 98 0 31 Aug 2022
Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits Marco Schreyer Timur Sattarov Damian Borth MLAU 36 15 0 26 Aug 2022
Semi-Supervised and Unsupervised Deep Visual Learning: A Survey Yanbei Chen Massimiliano Mancini Xiatian Zhu Zeynep Akata 47 114 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 31 19 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 40 12 0 18 Aug 2022
Private Estimation with Public Data Alex Bie Gautam Kamath Vikrant Singhal 36 28 0 16 Aug 2022
Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer Jicheng Li Anjana Bhat R. Barmaki ViT 27 5 0 01 Aug 2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning Yuanhao Xiong Ruochen Wang Minhao Cheng Felix X. Yu Cho-Jui Hsieh FedML DD 50 82 0 20 Jul 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms Ehsan Hallaji R. Razavi-Far M. Saif AAML FedML 27 13 0 05 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 75 102 0 30 Jun 2022
Differentially Private Federated Combinatorial Bandits with Constraints Sambhav Solanki Samhita Kanaparthy Sankarshan Damle Sujit Gujar FedML 29 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 27 36 0 10 Jun 2022
Differential Privacy: What is all the noise about? Roxana Dánger Mercaderes 38 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 56 22 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 48 109 0 06 May 2022
PhysioGAN: Training High Fidelity Generative Model for Physiological Sensor Readings M. Alzantot L. Garcia Mani B. Srivastava 27 1 0 25 Apr 2022
"Am I Private and If So, how Many?" -- Using Risk Communication Formats for Making Differential Privacy Understandable Daniel Franzen Saskia Nuñez von Voigt Peter Sorries Florian Tschorsch Claudia Muller-Birn Freie Universitat Berlin 34 9 0 08 Apr 2022
CTAB-GAN+: Enhancing Tabular Data Synthesis Zilong Zhao A. Kunar Robert Birke L. Chen 32 78 0 01 Apr 2022
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE Yuqing Zhu Yu-Xiang Wang 37 18 0 30 Mar 2022
Distributed data analytics Richard Mortier Hamed Haddadi S. S. Rodríguez Liang Wang 29 2 0 26 Mar 2022
A review of Generative Adversarial Networks for Electronic Health Records: applications, evaluation measures and data sources Ghadeer O. Ghosheh Jin Li T. Zhu 35 32 0 14 Mar 2022
One Parameter Defense -- Defending against Data Inference Attacks via Differential Privacy Dayong Ye Sheng Shen Tianqing Zhu B. Liu Wanlei Zhou MIACV 16 62 0 13 Mar 2022
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms Armando Angrisani Mina Doosti E. Kashefi 24 12 0 07 Mar 2022
Differentially Private Label Protection in Split Learning Xin Yang Jiankai Sun Yuanshun Yao Junyuan Xie Chong-Jun Wang FedML 47 36 0 04 Mar 2022
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data Oscar Giles Kasra Hosseini Grigorios Mingas Oliver Strickson Louise A. Bowler ... A. Heppenstall N. Lomax N. Malleson Martin O'Reilly Sebastian Vollmerteke 23 8 0 02 Mar 2022
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation Sina Sajadmanesh Ali Shahin Shamsabadi A. Bellet D. Gática-Pérez 40 63 0 02 Mar 2022
MIAShield: Defending Membership Inference Attacks via Preemptive Exclusion of Members Ismat Jarin Birhanu Eshete 32 9 0 02 Mar 2022
Does Label Differential Privacy Prevent Label Inference Attacks? Ruihan Wu Jinfu Zhou Kilian Q. Weinberger Chuan Guo 28 15 0 25 Feb 2022
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation Wenxiao Wang Alexander Levine S. Feizi AAML 20 60 0 05 Feb 2022
Differentially Private Graph Classification with GNNs Tamara T. Mueller Johannes C. Paetzold Chinmay Prabhakar Dmitrii Usynin Daniel Rueckert Georgios Kaissis 52 18 0 05 Feb 2022
Lessons from the AdKDD'21 Privacy-Preserving ML Challenge Eustache Diemert Romain Fabre Alexandre Gilotte Fei Jia Basile Leparmentier Jérémie Mary Zhonghua Qu Ugo Tanielian Hui Yang 59 6 0 31 Jan 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges Nuria Rodríguez-Barroso Daniel Jiménez López M. V. Luzón Francisco Herrera Eugenio Martínez-Cámara FedML 37 212 0 20 Jan 2022
Financial Vision Based Differential Privacy Applications Jun-Hao Chen Yi-Jen Wang Yun-Cheng Tsai Samuel Yen-Chi Chen FedML 21 1 0 28 Dec 2021
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning Vasisht Duddu S. Szyller Nadarajah Asokan 32 12 0 04 Dec 2021
Public Data-Assisted Mirror Descent for Private Model Training Ehsan Amid Arun Ganesh Rajiv Mathews Swaroop Indra Ramaswamy Shuang Song Thomas Steinke Vinith Suriyakumar Om Thakkar Abhradeep Thakurta 21 49 0 01 Dec 2021
Decentralized Federated Learning through Proxy Model Sharing Shivam Kalra Junfeng Wen Jesse C. Cresswell M. Volkovs Hamid R. Tizhoosh FedML 19 94 0 22 Nov 2021
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence Tianshi Cao Alex Bie Arash Vahdat Sanja Fidler Karsten Kreis SyDa DiffM 19 71 0 01 Nov 2021