Zhongzhu Chen

According to our database, Zhongzhu Chen authored at least 15 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Decision-making method with large-scale heterogeneous information using the preferred two-dimensional centroid and its application in forestland quality evaluation.

Huizhen Cai, Jian Lin, Zhongzhu Chen, Zeshui Xu

Comput. Appl. Math., July, 2026

A multi-stage integrated framework combining Shapley value and fuzzy cross-efficiency for dynamic benefit evaluation of regional forestry management entities.

Jian Lin, Zhongzhu Chen, Yujia Chen, Huang Yan, Zhiteng Chen, Yiwei Chen

Expert Syst. Appl., 2026

2025

Robust Representation Consistency Model via Contrastive Denoising.

Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Zhongjia Ba, Kui Ren, Jun Zhu, Anima Anandkumar

CoRR, January, 2025

Risk assessment and dynamic game analysis of sustainable cooperative afforestation.

Zhongzhu Chen, Jian Lin, Huizhen Cai, Zhiteng Chen

Appl. Soft Comput., 2025

Robust Representation Consistency Model via Contrastive Denoising.

Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Chaowei Xiao, Zhongjie Ba, Kui Ren, Jun Zhu, Anima Anandkumar

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Technical Note - Masking Anstreicher's linx Bound for Improved Entropy Bounds.

Zhongzhu Chen, Marcia Fampa, Jon Lee

Oper. Res., 2024

Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness.

Yiquan Li, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Bo Li, Chaowei Xiao

CoRR, 2024

Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness.

Yiquan Li, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Jiachen Lei, Bo Li, Chaowei Xiao

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts.

Kun Jin, Tongxin Yin, Zhongzhu Chen, Zeyu Sun, Xueru Zhang, Yang Liu, Mingyan Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

On Computing with Some Convex Relaxations for the Maximum-Entropy Sampling Problem.

Zhongzhu Chen, Marcia Fampa, Jon Lee

INFORMS J. Comput., 2023

DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing.

Jiawei Zhang, Zhongzhu Chen, Huan Zhang, Chaowei Xiao, Bo Li

Proceedings of the 32nd USENIX Security Symposium, 2023

DensePure: Understanding Diffusion Models for Adversarial Robustness.

Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Generalized Scaling for the Constrained Maximum-Entropy Sampling Problem.

Zhongzhu Chen, Marcia Fampa, Jon Lee

Proceedings of the SIAM Conference on Applied and Computational Discrete Algorithms, 2023

2022

DensePure: Understanding Diffusion Models towards Adversarial Robustness.

Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song

CoRR, 2022

2021

Mixing convex-optimization bounds for maximum-entropy sampling.

Zhongzhu Chen, Marcia Fampa, Amélie Lambert, Jon Lee

Math. Program., 2021