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Perceptual ad-blocking is a novel approach that detects online advertisements based on their visual content.
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Audio adversarial examples: Targeted attacks on speech-to-text. In DLS
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You Only Look Once: Unified, Real-Time Object Detection. In Conference on Computer Vision and Pattern Recognition (CVPR) . IEEE, 779–788
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Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song. 2017 · 2017
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A rotation and a translation suffice: Fooling CNNs with simple transformations
Logan Engstrom, Dimitris Tsipras, Ludwig Schmidt, and Aleksander Madry. 2017 · 2017
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On the (statistical) detection of adversarial examples
Kathrin Grosse, Praveen Manoharan, Nicolas Papernot, Michael Backes, and Patrick McDaniel. 2017a · 2017
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Edward Chou, Florian Tramèr, Giancarlo Pellegrino, and Dan Boneh. 2018 · 2018
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Justin Gilmer, Ryan P Adams, Ian Goodfellow, David Andersen, and George E Dahl. 2018a · 2018
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Black-box Adversarial Attacks with Limited Queries and Information. In International Conference on Machine Learning (ICML)
Andrew Ilyas, Logan Engstrom, Anish Athalye, and Jessy Lin. 2018 · 2018
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AdGraph: A Machine Learning Approach to Automatic and Effective Adblocking
Umar Iqbal, Zubair Shafiq, Peter Snyder, Shitong Zhu, Zhiyun Qian, and Benjamin Livshits. 2018 · 2018
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How Alexa Is Changing The Future Of Advertising
Ilker Koksal. 2018 · 2018
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Towards deep learning models resistant to adversarial attacks. In International Conference on Learning Representations (ICLR)
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu. 2018 · 2018
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Towards more intelligent ad blocking on the web
Paraska Oleksandr. 2018 · 2018
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The Future Of Advertising In Virtual Reality
George Paliy. 2018 · 2018
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Certified defenses against adversarial examples. In International Conference on Learning Representations (ICLR)
Aditi Raghunathan, Jacob Steinhardt, and Percy Liang. 2018 · 2018
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Joseph Redmon and Ali Farhadi. 2018 · 2018
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Adversarially robust generalization requires more data. In Advances in Neural Information Processing Systems . 5014–5026
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, and Aleksander Madry. 2018 · 2018
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Fooling OCR Systems with Adversarial Text Images
Congzheng Song and Vitaly Shmatikov. 2018 · 2018
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Ensemble adversarial training: Attacks and defenses. In International Conference on Learning Representations (ICLR)
Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, and Patrick McDaniel. 2018 · 2018
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Antoine Vastel, Peter Snyder, and Benjamin Livshits. 2018 · 2018
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Yet Another Text Captcha Solver: A Generative Adversarial Network Based Approach. In ACM SIGSAC Conference on Computer and Communications Security . ACM
Guixin Ye, Zhanyong Tang, Dingyi Fang, Zhanxing Zhu, Yansong Feng, Pengfei Xu, Xiaojiang Chen, and Zheng Wang. 2018 · 2018
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Stateful Detection of Black-Box Adversarial Attacks
Steven Chen, Nicholas Carlini, and David Wagner. 2019 · 2019
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Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep Learning
Panagiotis Tigas, Samuel T King, Benjamin Livshits, et al · 2019
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Adversarial Training and Robustness for Multiple Perturbations
Florian Tramèr and Dan Boneh. 2019 · 2019
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Perspectives from the Global Entertainment & Media Outlook 2018–2022
Ennèl van Eeden and Wilson Chow. 2018 · 2022
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