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The tremendous progress of autoencoders and generative adversarial networks (GANs) has led to their application to multiple critical tasks, such as fraud detection and sanitized data generation.
Poisoning Attacks against Support Vector Machines
Battista Biggio, Blaine Nelson, and Pavel Laskov · 2012
Earlier work this paper cites.
Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Explaining and Harnessing Adversarial Examples
Ian Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
Earlier work this paper cites.
Deep Learning Face Attributes in the Wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
Earlier work this paper cites.
Show and Tell: A Neural Image Caption Generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan · 2015
Earlier work this paper cites.
Adversarial Examples in the Physical World
Alexey Kurakin, Ian Goodfellow, and Samy Bengio · 2016
Earlier work this paper cites.
Differentially Private Mixture of Generative Neural Networks
Gergely Acs, Luca Melis, Claude Castelluccia, and Emiliano De Cristofaro · 2017
Earlier work this paper cites.
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods
Nicholas Carlini and David Wagner · 2017
Earlier work this paper cites.
Badnets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Grag · 2017
Earlier work this paper cites.
Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks
Marco Schreyer, Timur Sattarov, Damian Borth, Andreas Dengel, and Bernd Reimer · 2017
Cited alongside, same era.
Lossy Image Compression with Compressive Autoencoders
Lucas Theis, Wenzhe Shi, Andrew Cunningham, and Ferenc Huszár · 2017
Cited alongside, same era.
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye, Nicholas Carlini, and David A. Wagner · 2018
Cited alongside, same era.
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, and Bo Li · 2018
Cited alongside, same era.
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
Ali Shafahi, W Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, and Tom Goldstein · 2018
Cited alongside, same era.
PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees
James Jordon, Jinsung Yoon, and Mihaela van der Schaar · 2019
Later among the works it cites.
Trojaning Attack on Neural Networks
Yingqi Liu, Shiqing Ma, Yousra Aafer, Wen-Chuan Lee, Juan Zhai, Weihang Wang, and Xiangyu Zhang · 2019
Later among the works it cites.
GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs
Dingfan Chen, Ning Yu, Yang Zhang, and Mario Fritz · 2020
Closest in time.
BadNL: Backdoor Attacks Against NLP Models
Xiaoyi Chen, Ahmed Salem, Michael Backes, Shiqing Ma, and Yang Zhang · 2020
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Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning
Ahmed Salem, Apratim Bhattacharya, Michael Backes, Mario Fritz, and Yang Zhang · 2020
Closest in time.
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When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks
Octavian Suciu, Radu Mărginean, Yiğitcan Kaya, Hal Daumé III, and Tudor Dumitraş · 2018
Cited alongside, same era.
Differentially Private Generative Adversarial Network
Liyang Xie, Kaixiang Lin, Shu Wang, Fei Wang, and Jiayu Zhou · 2018
Cited alongside, same era.
LOGAN: Evaluating Privacy Leakage of Generative Models Using Generative Adversarial Networks
Jamie Hayes, Luca Melis, George Danezis, and Emiliano De Cristofaro · 2019
Cited alongside, same era.
Jinyuan Jia and Neil Zhenqiang Gong · 2019
Cited alongside, same era.
http://yann.lecun.com/exdb/mnist/
Cited in the paper.
https://www.cs.toronto.edu/~kriz/cifar.html
Cited in the paper.
Ahmed Salem, Rui Wen, Michael Backes, Shiqing Ma, and Yang Zhang · 2020
Closest in time.
You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion
Roei Schuster, Congzheng Song, Eran Tromer, and Vitaly Shmatikov · 2020
Closest in time.
Differentiable Augmentation for Data-Efficient GAN Training
Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, and Song Han · 2020
Closest in time.