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2020 – today
- 2023
[i5]Xi Wu, Joe Benassi, Yaqi Zhang, Uyeong Jang, James Foster, Stella Kim, Yujing Sun, Somesh Jha, John Cieslewicz, Jeffrey F. Naughton:
Holistic Cube Analysis: A Query Framework for Data Insights. CoRR abs/2302.00120 (2023)- [i4]Xi Wu, Xiangyao Yu, Shaleen Deep, Ahmed Mahmood, Uyeong Jang, Stratis Viglas, Somesh Jha, John Cieslewicz, Jeffrey F. Naughton:
Bilevel Relations and Their Applications to Data Insights. CoRR abs/2311.04824 (2023) - 2020
- [c4]Uyeong Jang, Susmit Jha, Somesh Jha:
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses. ICLR 2020
2010 – 2019
- 2019
- [i3]Uyeong Jang, Susmit Jha, Somesh Jha:
On Need for Topology Awareness of Generative Models. CoRR abs/1909.03334 (2019) - [i2]Lakshya Jain, Wilson Wu, Steven Chen, Uyeong Jang, Varun Chandrasekaran, Sanjit A. Seshia, Somesh Jha:
Generating Semantic Adversarial Examples with Differentiable Rendering. CoRR abs/1910.00727 (2019) - 2018
- [c3]Xi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh Jha:
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training. ICML 2018: 5330-5338 - [c2]Susmit Jha, Uyeong Jang, Somesh Jha, Brian Jalaian:
Detecting Adversarial Examples Using Data Manifolds. MILCOM 2018: 547-552 - 2017
- [c1]Uyeong Jang, Xi Wu, Somesh Jha:
Objective Metrics and Gradient Descent Algorithms for Adversarial Examples in Machine Learning. ACSAC 2017: 262-277 - [i1]Xi Wu, Uyeong Jang, Lingjiao Chen, Somesh Jha:
Manifold Assumption and Defenses Against Adversarial Perturbations. CoRR abs/1711.08001 (2017)
Coauthor Index
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