Search Results for author: Uyeong Jang

Found 4 papers, 0 papers with code

Generating Semantic Adversarial Examples with Differentiable Rendering

no code implementations2 Oct 2019 Lakshya Jain, Wilson Wu, Steven Chen, Uyeong Jang, Varun Chandrasekaran, Sanjit Seshia, Somesh Jha

In this paper we explore semantic adversarial examples (SAEs) where an attacker creates perturbations in the semantic space representing the environment that produces input for the ML model.

Autonomous Driving

On the Need for Topology-Aware Generative Models for Manifold-Based Defenses

no code implementations ICLR 2020 Uyeong Jang, Susmit Jha, Somesh Jha

These defenses rely on the assumption that data lie in a manifold of a lower dimension than the input space.

Data Augmentation

The Manifold Assumption and Defenses Against Adversarial Perturbations

no code implementations ICLR 2018 Xi Wu, Uyeong Jang, Lingjiao Chen, Somesh Jha

Interestingly, we find that a recent objective by Madry et al. encourages training a model that satisfies well our formal version of the goodness property, but has a weak control of points that are wrong but with low confidence.

Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training

no code implementations ICML 2018 Xi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh Jha

In this paper we study leveraging confidence information induced by adversarial training to reinforce adversarial robustness of a given adversarially trained model.

Adversarial Robustness

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