I tweet about #MachineLearning and #MachineLearningSecurity.
Joined April 2018
- Tweets 14
- Following 52
- Followers 182
- Likes 44
Photos and videos
Adversarial Machine Learning retweeted
5 Jul 2018
Just read this paper. Short summary: when thinking of defenses to adversarial examples in ML, think of the threat model carefully.
Nice paper. Also won the best paper award at ICML 2018 (@icmlconf )
Congrats to the authors!!
arxiv.org/abs/1802.00420
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Adversarial Machine Learning retweeted
1 Jun 2018
Adversarial robustness is not free: decrease in natural accuracy may be inevitable. Silver lining: robustness makes gradients semantically meaningful ( leads to adv. examples w/ GAN-like trajectories) arxiv.org/abs/1805.12152 (@tsiprasd @ShibaniSan @logan_engstrom @alex_m_turner)
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Adversarial Machine Learning retweeted
31 May 2018
Here's an article by @UofT about our new work on adversarial attacks on Face Detectors that help you preserve your privacy. news.engineering.utoronto.ca…
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Adversarial Machine Learning retweeted
30 May 2018
Think BatchNorm helps training due to reducing internal covariate shift? Think again. (What BatchNorm *does* seem to do though, both empirically and in theory, is to smoothen out the optimization landscape.) (with @ShibaniSan @tsiprasd @andrew_ilyas) arxiv.org/abs/1805.11604
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Adversarial Machine Learning retweeted
28 May 2018
Excited by this direction of formal investigation for adversarial defences: Adversarial examples from computational constraints, Bubeck et al arxiv.org/abs/1805.10204
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Adversarial Machine Learning retweeted
24 May 2018
"No pixels are manipulated in this talk. No pandas are harmed..."
Great ways to differentiate your talk from the rest of talks on adversarial examples... no more pandas please 😀
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Adversarial Machine Learning retweeted
24 May 2018
I'm speaking at the 1st Deep Learning and Security workshop (co-located with @IEEESSP ) at 1:30 today: ieee-security.org/TC/SPW2018… I'll discuss research into defenses against adversarial examples, including future directions. Slides and lecture notes here: iangoodfellow.com/slides/201…
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Adversarial Machine Learning retweeted
22 May 2018
This paper shows how to make adversarial examples with GANs. No need for a norm ball constraint. They look unperturbed to a human observer but break a model trained to resist large perturbations. arxiv.org/pdf/1805.07894.pdf
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Adversarial Machine Learning retweeted
12 May 2018
LaVAN: Localized and Visible Adversarial Noise. A method to generate adversarial noise which is confined to small, localized patch of the image without covering any main objects of the image.
arxiv.org/abs/1801.02608
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Adversarial Machine Learning retweeted
11 May 2018
Two papers accepted to ICML 2018. Congrats to all my amazing co-authors. Both on adversarial ML. The arxiv
version of the papers are up, but we will update it soon based on reviewer comments.
Arxiv versions: arxiv.org/abs/1711.08001 and
arxiv.org/abs/1706.03922
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30 Apr 2018
A detailed post on privacy in machine learning describing why do we need private ML algorithms, and how can we leverage PATE framework to achieve the same (by @NicolasPapernot and @goodfellow_ian) cleverhans.io/privacy/2018/0…
#MachineLearning
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30 Apr 2018
Securing Distributed Machine Learning in High Dimensions
arxiv.org/abs/1804.10140
#MachineLearningSecurity #AdversarialML
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29 Apr 2018
IBM Ireland just released "The Adversarial Robustness Toolbox: Securing AI Against Adversarial Threats". This library will allow rapid crafting and analysis of attacks and defense methods for machine learning models.
ibm.com/blogs/research/2018/…
#MachineLearningSecurity #AdversarialML