Chen Liu

24 papers A* 6Journal 18
YearRankTypeTitle / Venue / Authors
2026 J jnl
Sparse-PGD: A Unified Framework for Sparse Adversarial Perturbations Generation.
IEEE Trans. Pattern Anal. Mach. Intell.
Xuyang Zhong, Chen Liu
2025 J jnl
DualOptim: Enhancing Efficacy and Stability in Machine Unlearning with Dual Optimizers.
CoRR
Xuyang Zhong, Haochen Luo, Chen Liu
2025 J jnl
Fast Adversarial Training against Sparse Attacks Requires Loss Smoothing.
CoRR
Xuyang Zhong, Yixiao Huang, Chen Liu
2025 J jnl
Toward Mitigating Architecture Overfitting on Distilled Datasets.
IEEE Trans. Neural Networks Learn. Syst.
Xuyang Zhong, Chen Liu
2024 J jnl
Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density.
CoRR
Shuangqi Li, Chen Liu, Tong Zhang, Hieu Le, Sabine Süsstrunk, Mathieu Salzmann
2024 J jnl
Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density.
Trans. Mach. Learn. Res.
Shuangqi Li, Chen Liu, Tong Zhang, Hieu Le, Sabine Süsstrunk, Mathieu Salzmann
2024 J jnl
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training.
J. Mach. Learn. Res.
Chen Liu, Zhichao Huang, Mathieu Salzmann, Tong Zhang, Sabine Süsstrunk
2024 J jnl
Towards Efficient Training and Evaluation of Robust Models against l
CoRR
Xuyang Zhong, Yixiao Huang, Chen Liu
2024 A* conf
Towards Efficient Training and Evaluation of Robust Models against l0 Bounded Adversarial Perturbations.
ICML
Xuyang Zhong, Yixiao Huang, Chen Liu
2023 J jnl
Fast Adversarial Training With Adaptive Step Size.
IEEE Trans. Image Process.
Zhichao Huang, Yanbo Fan, Chen Liu, Weizhong Zhang, Yong Zhang, Mathieu Salzmann, Sabine Süsstrunk, Jue Wang
2023 J jnl
Towards Mitigating Architecture Overfitting in Dataset Distillation.
CoRR
Xuyang Zhong, Chen Liu
2023 A* conf
Towards Stable and Efficient Adversarial Training against l
ICML
Yulun Jiang, Chen Liu, Zhichao Huang, Mathieu Salzmann, Sabine Süsstrunk
2023 J jnl
Training Provably Robust Models by Polyhedral Envelope Regularization.
IEEE Trans. Neural Networks Learn. Syst.
Chen Liu, Mathieu Salzmann, Sabine Süsstrunk
2022 J jnl
Fast Adversarial Training with Adaptive Step Size.
CoRR
Zhichao Huang, Yanbo Fan, Chen Liu, Weizhong Zhang, Yong Zhang, Mathieu Salzmann, Sabine Süsstrunk, Jue Wang
2022 A* conf
Robust Binary Models by Pruning Randomly-initialized Networks.
NeurIPS
Chen Liu, Ziqi Zhao, Sabine Süsstrunk, Mathieu Salzmann
2022 J jnl
Robust Binary Models by Pruning Randomly-initialized Networks.
CoRR
Chen Liu, Ziqi Zhao, Sabine Süsstrunk, Mathieu Salzmann
2021 J jnl
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training.
CoRR
Chen Liu, Zhichao Huang, Mathieu Salzmann, Tong Zhang, Sabine Süsstrunk
2020 A* conf
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them.
NeurIPS
Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk
2020 J jnl
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them.
CoRR
Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk
2019 A* conf
Finding Mixed Nash Equilibria of Generative Adversarial Networks.
ICML
Ya-Ping Hsieh, Chen Liu, Volkan Cevher
2019 A* conf
On Certifying Non-Uniform Bounds against Adversarial Attacks.
ICML
Chen Liu, Ryota Tomioka, Volkan Cevher
2019 J jnl
On Certifying Non-uniform Bound against Adversarial Attacks.
CoRR
Chen Liu, Ryota Tomioka, Volkan Cevher
2019 J jnl
On Certifying Robust Models by Polyhedral Envelope.
CoRR
Chen Liu, Mathieu Salzmann, Sabine Süsstrunk
2018 J jnl
Finding Mixed Nash Equilibria of Generative Adversarial Networks.
CoRR
Ya-Ping Hsieh, Chen Liu, Volkan Cevher