Analyzing the Robustness of Nearest Neighbors to Adversarial Examples

arXiv e-Print archive - 2017 via Local Bibsonomy

Keywords: dblp

arXiv e-Print archive - 2017 via Local Bibsonomy

Keywords: dblp

On the Suitability of Lp-Norms for Creating and Preventing Adversarial Examples

Conference and Computer Vision and Pattern Recognition - 2018 via Local Bibsonomy

Keywords: dblp

Conference and Computer Vision and Pattern Recognition - 2018 via Local Bibsonomy

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Learning to Compose Domain-Specific Transformations for Data Augmentation.

Neural Information Processing Systems Conference - 2017 via Local dblp

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Neural Information Processing Systems Conference - 2017 via Local dblp

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Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning

arXiv e-Print archive - 2018 via Local arXiv

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arXiv e-Print archive - 2018 via Local arXiv

Keywords: cs.LG, stat.ML

Towards Imperceptible and Robust Adversarial Example Attacks against Neural Networks

arXiv e-Print archive - 2018 via Local arXiv

Keywords: cs.LG, cs.CR, stat.ML

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arXiv e-Print archive - 2018 via Local arXiv

Keywords: cs.LG, cs.CR, stat.ML

On Calibration of Modern Neural Networks

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG

Interpretation of Neural Networks is Fragile

arXiv e-Print archive - 2017 via Local Bibsonomy

Keywords: dblp

arXiv e-Print archive - 2017 via Local Bibsonomy

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Spatially Transformed Adversarial Examples

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

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Attacking the Madry Defense Model with $L_1$-based Adversarial Examples

arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.CR, cs.LG

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.CR, cs.LG

Robustness of Rotation-Equivariant Networks to Adversarial Perturbations

arXiv e-Print archive - 2018 via Local Bibsonomy

Keywords: dblp

arXiv e-Print archive - 2018 via Local Bibsonomy

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Geometric robustness of deep networks: analysis and improvement

arXiv e-Print archive - 2017 via Local Bibsonomy

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arXiv e-Print archive - 2017 via Local Bibsonomy

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Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

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ADef: an Iterative Algorithm to Construct Adversarial Deformations

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

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Adversarial Reprogramming of Neural Networks

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

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On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

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Convex Learning with Invariances

Neural Information Processing Systems Conference - 2007 via Local Bibsonomy

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Neural Information Processing Systems Conference - 2007 via Local Bibsonomy

Keywords: dblp

Boosting Adversarial Attacks With Momentum

Conference and Computer Vision and Pattern Recognition - 2018 via Local Bibsonomy

Keywords: dblp

Conference and Computer Vision and Pattern Recognition - 2018 via Local Bibsonomy

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Provable defenses against adversarial examples via the convex outer adversarial polytope

arXiv e-Print archive - 2017 via Local Bibsonomy

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arXiv e-Print archive - 2017 via Local Bibsonomy

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There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits)

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

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Adversarially Robust Generalization Requires More Data

Neural Information Processing Systems Conference - 2018 via Local Bibsonomy

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Neural Information Processing Systems Conference - 2018 via Local Bibsonomy

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Protecting JPEG Images Against Adversarial Attacks

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

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Out-distribution training confers robustness to deep neural networks

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

Keywords: dblp

Defense Against Universal Adversarial Perturbations

Conference and Computer Vision and Pattern Recognition - 2018 via Local Bibsonomy

Keywords: dblp

Conference and Computer Vision and Pattern Recognition - 2018 via Local Bibsonomy

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Adversarial Defense based on Structure-to-Signal Autoencoders

arXiv e-Print archive - 2018 via Local Bibsonomy

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arXiv e-Print archive - 2018 via Local Bibsonomy

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Adversarial Attacks on Neural Network Policies

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CR, stat.ML

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CR, stat.ML

Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CV, cs.CR, cs.GT, cs.LG

Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey

arXiv e-Print archive - 2018 via Local arXiv

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arXiv e-Print archive - 2018 via Local arXiv

Keywords: cs.CV

Adversarial Examples: Attacks and Defenses for Deep Learning

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CR, cs.CV, stat.ML

Adversarial Diversity and Hard Positive Generation

arXiv e-Print archive - 2016 via Local arXiv

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arXiv e-Print archive - 2016 via Local arXiv

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Measuring Neural Net Robustness with Constraints

arXiv e-Print archive - 2016 via Local arXiv

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arXiv e-Print archive - 2016 via Local arXiv

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Robustness of classifiers: from adversarial to random noise

arXiv e-Print archive - 2016 via Local arXiv

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.LG, cs.CV, stat.ML

A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples

arXiv e-Print archive - 2016 via Local arXiv

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.LG, stat.ML

Certified Defenses against Adversarial Examples

arXiv e-Print archive - 2018 via Local arXiv

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arXiv e-Print archive - 2018 via Local arXiv

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Parseval Networks: Improving Robustness to Adversarial Examples

International Conference on Machine Learning - 2017 via Local Bibsonomy

Keywords: dblp

International Conference on Machine Learning - 2017 via Local Bibsonomy

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Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality

arXiv e-Print archive - 2018 via Local arXiv

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arXiv e-Print archive - 2018 via Local arXiv

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Detecting Adversarial Samples from Artifacts

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

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Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

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On the (Statistical) Detection of Adversarial Examples

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CR, cs.LG, stat.ML

Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CR, cs.CV

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CR, cs.CV

Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation.

Neural Information Processing Systems Conference - 2017 via Local dblp

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Neural Information Processing Systems Conference - 2017 via Local dblp

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Adversarial Vulnerability of Neural Networks Increases With Input Dimension

arXiv e-Print archive - 2018 via Local arXiv

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arXiv e-Print archive - 2018 via Local arXiv

Keywords: stat.ML, cs.CV, cs.LG, 68T45, I.2.6

Biologically inspired protection of deep networks from adversarial attacks

arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.LG, q-bio.NC

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.LG, q-bio.NC

Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CV, cs.CR, cs.LG

Generative adversarial networks uncover epidermal regulators and predict single cell perturbations

bioRxiv: The preprint server for biology - 2018 via Local CrossRef

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bioRxiv: The preprint server for biology - 2018 via Local CrossRef

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Certifying Some Distributional Robustness with Principled Adversarial Training

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

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Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization

arXiv e-Print archive - 2015 via Local arXiv

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arXiv e-Print archive - 2015 via Local arXiv

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Distributional Smoothing with Virtual Adversarial Training

arXiv e-Print archive - 2015 via Local arXiv

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arXiv e-Print archive - 2015 via Local arXiv

Keywords: stat.ML, cs.LG

Efficient Defenses Against Adversarial Attacks

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG

Ensemble Robustness of Deep Learning Algorithms

arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.LG, cs.CV, stat.ML

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.LG, cs.CV, stat.ML

Towards Robust Neural Networks via Random Self-ensemble

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CR, stat.ML

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CR, stat.ML

Towards Reverse-Engineering Black-Box Neural Networks

arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.CR, cs.CV, cs.LG

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.CR, cs.CV, cs.LG

Comment on "Biologically inspired protection of deep networks from adversarial attacks"

arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.LG, q-bio.NC

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.LG, q-bio.NC

ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models

arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.CR, cs.LG

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arXiv e-Print archive - 2017 via Local arXiv

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Adversarial Robustness: Softmax versus Openmax

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CV

The Limitations of Deep Learning in Adversarial Settings

arXiv e-Print archive - 2015 via Local arXiv

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arXiv e-Print archive - 2015 via Local arXiv

Keywords: cs.CR, cs.LG, cs.NE, stat.ML

A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CV, cs.NE, stat.ML

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.LG, cs.CV, cs.NE, stat.ML

Adversarial examples in the physical world

arXiv e-Print archive - 2016 via Local arXiv

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.CV, cs.CR, cs.LG, stat.ML

NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles

arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CV, cs.AI, cs.CR

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: cs.CV, cs.AI, cs.CR

Adversarial Machine Learning at Scale

arXiv e-Print archive - 2016 via Local arXiv

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.CV, cs.CR, cs.LG, stat.ML

Delving into Transferable Adversarial Examples and Black-box Attacks

arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.LG

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.LG

Universal adversarial perturbations

arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.CV, cs.AI, cs.LG, stat.ML

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.CV, cs.AI, cs.LG, stat.ML

Towards Evaluating the Robustness of Neural Networks

arXiv e-Print archive - 2016 via Local arXiv

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.CR, cs.CV

Towards Deep Learning Models Resistant to Adversarial Attacks

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.LG, cs.NE

Explaining and Harnessing Adversarial Examples

arXiv e-Print archive - 2014 via Local arXiv

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arXiv e-Print archive - 2014 via Local arXiv

Keywords: stat.ML, cs.LG

Ensemble Adversarial Training: Attacks and Defenses

arXiv e-Print archive - 2017 via Local arXiv

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arXiv e-Print archive - 2017 via Local arXiv

Keywords: stat.ML, cs.CR, cs.LG

Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

arXiv e-Print archive - 2015 via Local arXiv

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arXiv e-Print archive - 2015 via Local arXiv

Keywords: cs.CR, cs.LG, cs.NE, stat.ML

Simple Black-Box Adversarial Perturbations for Deep Networks

arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.LG, cs.CR, stat.ML

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arXiv e-Print archive - 2016 via Local arXiv

Keywords: cs.LG, cs.CR, stat.ML

Intriguing properties of neural networks

arXiv e-Print archive - 2013 via Local arXiv

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arXiv e-Print archive - 2013 via Local arXiv

Keywords: cs.CV, cs.LG, cs.NE

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