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Collaborative machine learning settings like federated learning can be susceptible to adversarial interference and attacks.
Nonlinear total variation based noise removal algorithms
Leonid I Rudin, Stanley Osher, and Emad Fatemi · 1992
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Faces—a database of facial expressions in young, middle-aged, and older women and men: Development and validation
Natalie C Ebner, Michaela Riediger, and Ulman Lindenberger · 2010
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Spoofing 2d face recognition systems with 3d masks
Nesli Erdogmus and Sébastien Marcel · 2013
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The multimodal brain tumor image segmentation benchmark (brats)
Bjoern H Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, et al · 2014
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Model inversion attacks that exploit confidence information and basic countermeasures
Matt Fredrikson, Somesh Jha, and Thomas Ristenpart · 2015
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Predicting stock market index using fusion of machine learning techniques
Jigar Patel, Sahil Shah, Priyank Thakkar, and Ketan Kotecha · 2015
Earlier work this paper cites.
Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
Earlier work this paper cites.
You are who you know and how you behave: Attribute inference attacks via users’ social friends and behaviors
Neil Zhenqiang Gong and Bin Liu · 2016
Earlier work this paper cites.
Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
Earlier work this paper cites.
Federated learning: Strategies for improving communication efficiency
Jakub Konečnỳ, H Brendan McMahan, Felix X Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon · 2016
Earlier work this paper cites.
Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning
Pranav Rajpurkar, Jeremy Irvin, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Ding, Aarti Bagul, Curtis Langlotz, Katie Shpanskaya, et al · 2017
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Pairwise confusion for fine-grained visual classification
Abhimanyu Dubey, Otkrist Gupta, Pei Guo, Ramesh Raskar, Ryan Farrell, and Nikhil Naik · 2018
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Self-supervised learning for medical image analysis using image context restoration
Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, and Daniel Rueckert · 2019
Cited alongside, same era.
Model inversion attacks against collaborative inference
Zecheng He, Tianwei Zhang, and Ruby B Lee · 2019
Cited alongside, same era.
Decoupled weight decay regularization, 2019
Ilya Loshchilov and Frank Hutter · 2019
Cited alongside, same era.
Exploiting unintended feature leakage in collaborative learning
Luca Melis, Congzheng Song, Emiliano De Cristofaro, and Vitaly Shmatikov · 2019
Cited alongside, same era.
Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning
Milad Nasr, Reza Shokri, and Amir Houmansadr · 2019
Cited alongside, same era.
Dba: Distributed backdoor attacks against federated learning
A survey on anti-spoofing methods for facial recognition with rgb cameras of generic consumer devices
Zuheng Ming, Muriel Visani, Muhammad Muzzamil Luqman, and Jean-Christophe Burie · 2020
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A survey on distributed machine learning
Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg, Tim Verbelen, and Jan S Rellermeyer · 2020
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The secret revealer: Generative model-inversion attacks against deep neural networks
Yuheng Zhang, Ruoxi Jia, Hengzhi Pei, Wenxiao Wang, Bo Li, and Dawn Song · 2020
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idlg: Improved deep leakage from gradients
Bo Zhao, Konda Reddy Mopuri, and Hakan Bilen · 2020
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Deep leakage from gradients
Ligeng Zhu and Song Han · 2020
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Chulin Xie, Keli Huang, Pin-Yu Chen, and Bo Li · 2019
Cited alongside, same era.
Medical breast ultrasound image segmentation by machine learning
Yuan Xu, Yuxin Wang, Jie Yuan, Qian Cheng, Xueding Wang, and Paul L Carson · 2019
Cited alongside, same era.
Are all layers created equal?, 2019
Chiyuan Zhang, Samy Bengio, and Yoram Singer · 2019
Cited alongside, same era.
A machine learning algorithm to estimate sarcopenia on abdominal ct
Joseph E Burns, Jianhua Yao, Didier Chalhoub, Joseph J Chen, and Ronald M Summers · 2020
Cited alongside, same era.
New machine learning method for image-based diagnosis of covid-19
Mohamed Abd Elaziz, Khalid M Hosny, Ahmad Salah, Mohamed M Darwish, Songfeng Lu, and Ahmed T Sahlol · 2020
Cited alongside, same era.
Inverting gradients–how easy is it to break privacy in federated learning?
Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, and Michael Moeller · 2020
Cited alongside, same era.
Georgios Kaissis, Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, Ionésio Lima, Jason Mancuso, Friederike Jungmann, Marc-Matthias Steinborn, et al · 2021
Later among the works it cites.
Fedbn: Federated learning on non-iid features via local batch normalization
Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, and Qi Dou · 2021
Later among the works it cites.
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning
Dmitrii Usynin, Alexander Ziller, Marcus Makowski, Rickmer Braren, Daniel Rueckert, Ben Glocker, Georgios Kaissis, and Jonathan Passerat-Palmbach · 2021
Later among the works it cites.
See through gradients: Image batch recovery via gradinversion
Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M Alvarez, Jan Kautz, and Pavlo Molchanov · 2021
Later among the works it cites.
Differentially private federated deep learning for multi-site medical image segmentation
Alexander Ziller, Dmitrii Usynin, Nicolas Remerscheid, Moritz Knolle, Marcus Makowski, Rickmer Braren, Daniel Rueckert, and Georgios Kaissis · 2021
Later among the works it cites.
Do gradient inversion attacks make federated learning unsafe?, 2022
Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona G. Flores, Jan Kautz, Daguang Xu, and Holger R. Roth · 2022
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