Zhehui Chen - RankMe

24 papers A* 3A 2Journal 13Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Augmenting Question Answering with A Hybrid RAG Approach. CoRR Tianyi Yang, Nashrah Haque, Vaishnave Jonnalagadda, Yuya Jeremy Ong, Zhehui Chen, Yanzhao Wu, Lei Yu, Divyesh Jadav, Wenqi Wei
2025	—	`conf`	Augmenting Question Answering with A Hybrid RAG Approach. CogMI Tianyi Yang, Nashrah Haque, Vaishnave Jonnalagadda, Yuya Jeremy Ong, Zhehui Chen, Yanzhao Wu, Lei Yu, Divyesh Jadav, Wenqi Wei
2025	J	`jnl`	LGAT: A novel model for multivariate time series anomaly detection with improved anomaly transformer and learning graph structures. Neurocomputing Mi Wen, Zhehui Chen, Yun Xiong, Yichuan Zhang
2024	—	`conf`	Boosting Imperceptibility of Stable Diffusion-based Adversarial Examples Generation with Momentum. TPS-ISA Nashrah Haque, Xiang Li, Zhehui Chen, Yanzhao Wu, Lei Yu, Arun Iyengar, Wenqi Wei
2024	J	`jnl`	Boosting Imperceptibility of Stable Diffusion-based Adversarial Examples Generation with Momentum. CoRR Nashrah Haque, Xiang Li, Zhehui Chen, Yanzhao Wu, Lei Yu, Arun Iyengar, Wenqi Wei
2024	J	`jnl`	Solving Sparse & High-Dimensional-Output Regression via Compression. CoRR Renyuan Li, Zhehui Chen, Guanyi Wang
2024	A*	`conf`	Solving Sparse \& High-Dimensional-Output Regression via Compression. NeurIPS Renyuan Li, Zhehui Chen, Guanyi Wang
2023	—	`conf`	Invisible Watermarking for Audio Generation Diffusion Models. TPS-ISA Xirong Cao, Xiang Li, Divyesh Jadav, Yanzhao Wu, Zhehui Chen, Chen Zeng, Wenqi Wei
2023	J	`jnl`	Invisible Watermarking for Audio Generation Diffusion Models. CoRR Xirong Cao, Xiang Li, Divyesh Jadav, Yanzhao Wu, Zhehui Chen, Chen Zeng, Wenqi Wei
2023	A*	`conf`	Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. NeurIPS Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
2023	J	`jnl`	Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. CoRR Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
2022	J	`jnl`	APIK: Active Physics-Informed Kriging Model with Partial Differential Equations. SIAM/ASA J. Uncertain. Quantification Jialei Chen, Zhehui Chen, Chuck Zhang, C. F. Jeff Wu
2021	A	`conf`	Learning to Defend by Learning to Attack. AISTATS Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao
2021	—	`—`	Modern Statistical Methods for Optimization and Change-point Detection. Zhehui Chen
2020	J	`jnl`	APIK: Active Physics-Informed Kriging Model with Partial Differential Equations. CoRR Jialei Chen, Zhehui Chen, Chuck Zhang, C. F. Jeff Wu
2019	—	`conf`	Learning to Defense by Learning to Attack. DGS@ICLR Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao
2019	—	`conf`	On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. ICLR (Poster) Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao
2019	A	`conf`	On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition. AISTATS Zhehui Chen, Xingguo Li, Lin Yang, Jarvis D. Haupt, Tuo Zhao
2018	J	`jnl`	Learning to Defense by Learning to Attack. CoRR Zhehui Chen, Haoming Jiang, Bo Dai, Tuo Zhao
2018	J	`jnl`	On Computation and Generalization of GANs with Spectrum Control. CoRR Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao
2018	J	`jnl`	On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization. CoRR Zhehui Chen, Xingguo Li, Lin F. Yang, Jarvis D. Haupt, Tuo Zhao
2018	J	`jnl`	Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations. CoRR Tianyi Liu, Zhehui Chen, Enlu Zhou, Tuo Zhao
2017	J	`jnl`	Online Multiview Representation Learning: Dropping Convexity for Better Efficiency. CoRR Zhehui Chen, Forest L. Yang, Chris Junchi Li, Tuo Zhao
2017	A*	`conf`	Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability. ICML Zhehui Chen, Lin F. Yang, Chris Junchi Li, Tuo Zhao