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1GitHub - BorealisAI/advertorch: A Toolbox for Adversarial Robustness Research
https://github.com/BorealisAI/advertorch
4 years ago by @topel
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pytorch
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1GitHub - lyakaap/VAT-pytorch: Virtual Adversarial Training (VAT) implementation for PyTorch
Virtual Adversarial Training (VAT) implementation for PyTorch - lyakaap/VAT-pytorch
4 years ago by @topel
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pytorch
semisup
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1Toolbox to generate adversarial examples
https://github.com/advboxes/AdvBox
4 years ago by @topel
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1Adversarial Robustness - Theory and Practice
Adversarial Robustness - Theory and Practice NeurIPS Chapter Tutorial
5 years ago by @kirk86
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robustness
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1Interspeech 2019 Tutorial: Adversarial attacks on speech systems
http://www.cs.cmu.edu/~bhiksha/interspeech2019/
5 years ago by @topel
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1cleverhans/examples/adversarial_asr at master · tensorflow/cleverhans · GitHub
https://github.com/tensorflow/cleverhans/tree/master/examples/adversarial_asr
5 years ago by @topel
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1Imperceptible, Robust and Targeted Adversarial Examples for Automatic Speech Recognition
http://cseweb.ucsd.edu/~yaq007/imperceptible-robust-adv.html
5 years ago by @topel
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1Can variational autoencoders (VAE) beat generative adversarial networks (GAN) in image generation or in doing other tasks on an image? - Quora
https://www.quora.com/Can-variational-autoencoders-VAE-beat-generative-adversarial-networks-GAN-in-image-generation-or-in-doing-other-tasks-on-an-image
5 years ago by @becker
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autoencoder
auto
encoder
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gan
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afcs
varitionalautoencoderautoencodervargangenerativeadversarialmodelvsbeatimagegenerationafcs
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1Dataset Shift in Machine Learning (Neural Information Processing)
http://www.acad.bg/ebook/ml/The.MIT.Press.Dataset.Shift.in.Machine.Learning.Feb.2009.eBook-DDU.pdf
5 years ago by @kirk86
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anomaly-detection
book
machine-learning
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1A systematic framework for natural perturbations from videos
https://modestyachts.github.io/natural-perturbations-website/results.html
5 years ago by @kirk86
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1A systematic framework for natural perturbations from videos
https://modestyachts.github.io/natural-perturbations-website/
5 years ago by @kirk86
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blog
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1nalisnick_OxCSML_talk
http://people.ds.cam.ac.uk/etn22/nalisnick_OxCSML_talk.pdf
5 years ago by @kirk86
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adversarial
anomaly-detection
flows
optimal-transport
probability
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adversarialanomaly-detectionflowsoptimal-transportprobabilityrobustness
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1Adversarial Multi-Player Bandits (Nicolò Cesa-Bianchi and Ohad Shamir) | UW MSR 2015 Summer Institute on Stochastic Processes, Learning, and Optimization Open Problems
https://mssi2015.wordpress.com/2015/06/10/adversarial-multi-player-bandits-nicolo-cesa-bianchi-and-ohad-shamir/
5 years ago by @kirk86
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1secML
https://secml.github.io/
5 years ago by @kirk86
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book
course
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1GitHub - bethgelab/foolbox: Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, Keras, …
Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, Keras, … - bethgelab/foolbox
5 years ago by @topel
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1FGSM-Keras/targeted_attack.ipynb at master · soumyac1999/FGSM-Keras · GitHub
https://github.com/soumyac1999/FGSM-Keras/blob/master/targeted_attack.ipynb
5 years ago by @topel
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1Attacking My MNIST Neural Net With Adversarial Examples
http://everettsprojects.com/2018/01/30/mnist-adversarial-examples.html
5 years ago by @topel
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adversarial
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1cleverhans/cleverhans_tutorials at master · tensorflow/cleverhans · GitHub
https://github.com/tensorflow/cleverhans/tree/master/cleverhans_tutorials
5 years ago by @topel
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adversarial
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1Paper Discussion: Explaining and harnessing adversarial examples
https://medium.com/@mahendrakariya/paper-discussion-explaining-and-harnessing-adversarial-examples-908a1b7123b5
5 years ago by @topel
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1Elon Musk: Tesla Autopilot | Artificial Intelligence (AI) Podcast - YouTube
Elon Musk is the CEO of Tesla, SpaceX, Neuralink, and a co-founder of several other companies. This conversation is part of the Artificial Intelligence podca... Elon comments on adversarial attack at 26:45
5 years ago by @straybird321
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2Adversarial Robustness through Regularization: A Second-Order Approach
A. Ma, F. Faghri, and A. Farahmand. (2020)cite arxiv:2004.01832.
4 years ago by @kirk86
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adversarial
regularisation
robustness
adversarialregularisationrobustness
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3On Biased Random Walks, Corrupted Intervals, and Learning Under Adversarial Design
D. Berend, A. Kontorovich, L. Reyzin, and T. Robinson. (2020)cite arxiv:2003.13561Comment: 18 pages.
4 years ago by @kirk86
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adversarial
randomized
readings
robustness
sampling
adversarialrandomizedreadingsrobustnesssampling
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2Sign Bits Are All You Need for Black-Box Attacks
A. Al-Dujaili, and U. O'Reilly. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
adversarialiclr2020
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2Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing
J. Jia, X. Cao, B. Wang, and N. Gong. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
robustness
adversarialiclr2020robustness
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1GAT: Generative Adversarial Training for Adversarial Example Detection and Classification
X. Yin, S. Kolouri, and G. Rohde. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
adversarialiclr2020
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2On the Need for Topology-Aware Generative Models for Manifold-Based Defenses
U. Jang, S. Jha, and S. Jha. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
generative-models
iclr2020
manifolds
topology
adversarialgenerative-modelsiclr2020manifoldstopology
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2Intriguing Properties of Adversarial Training at Scale
C. Xie, and A. Yuille. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
adversarialiclr2020
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2Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
T. Pang*, K. Xu*, and J. Zhu. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
robustness
adversarialiclr2020robustness
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1Implicit Bias of Gradient Descent based Adversarial Training on Separable Data
Y. Li, E. X.Fang, H. Xu, and T. Zhao. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
optimization
adversarialiclr2020optimization
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2Enhancing Transformation-Based Defenses Against Adversarial Attacks with a Distribution Classifier
C. Kou, H. Lee, E. Chang, and T. Ng. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
probability
robustness
adversarialiclr2020probabilityrobustness
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1Certified Defenses for Adversarial Patches
P. yeh Chiang*, R. Ni*, A. Abdelkader, C. Zhu, C. Studor, and T. Goldstein. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
robustness
adversarialiclr2020robustness
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2Universal Approximation with Certified Networks
M. Baader, M. Mirman, and M. Vechev. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
robustness
adversarialiclr2020robustness
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2Adversarial AutoAugment
X. Zhang, Q. Wang, J. Zhang, and Z. Zhong. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
augmentation
iclr2020
adversarialaugmentationiclr2020
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2Provable robustness against all adversarial $l_p$-perturbations for $p1$
F. Croce, and M. Hein. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
robustness
adversarialiclr2020robustness
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2Enhancing Adversarial Defense by k-Winners-Take-All
C. Xiao, P. Zhong, and C. Zheng. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
robustness
adversarialiclr2020robustness
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3Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
D. Wu, Y. Wang, S. Xia, J. Bailey, and X. Ma. International Conference on Learning Representations, (2020)
4 years ago by @kirk86
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adversarial
iclr2020
adversarialiclr2020
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1Reduced-Variance Payoff Estimation in Adversarial Bandit Problems
L. Kocsis, and {. Szepesvári. Proceedings of the ECML-2005 Workshop on Reinforcement Learning in Non-Stationary Environments, (2005)
4 years ago by @csaba
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adversarial
bandits
learning,
online
setting,
adversarialbanditslearning,onlinesetting,
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1The Online Loop-free Stochastic Shortest-Path Problem
G. Neu, A. György, and {. Szepesvári. COLT, page 231--243. (June 2010)
4 years ago by @csaba
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MDPs,
adversarial
finite
learning,
online
path
problem
setting,
shortest
MDPs,adversarialfinitelearning,onlinepathproblemsetting,shortest
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1Toward a Classification of Finite Partial-Monitoring Games
G. Bartók, D. Pál, and {. Szepesvári. ALT, page 224--238. (October 2010)
4 years ago by @csaba
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adversarial
game
information
learning,
online
partial
setting,
theory,
adversarialgameinformationlearning,onlinepartialsetting,theory,
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1The adversarial stochastic shortest path problem with unknown transition probabilities
G. Neu, A. György, and {. Szepesvári. AISTATS, page 805--813. (April 2012)
4 years ago by @csaba
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MDPs,
adversarial
finite
learning,
online
path
problem,
setting,
shortest
theory
MDPs,adversarialfinitelearning,onlinepathproblem,setting,shortesttheory
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