Zhengmian Hu

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 25

Top Topics

Doubly Stochastic

Top Venues

Publications

Yihan Wu, Ruibo Chen, Zhengmian Hu, Yanshuo Chen, Junfeng Guo, Hongyang Zhang, Heng Huang
Distortion-free Watermarks are not Truly Distortion-free under Watermark Key Collisions. CoRR (2024)
Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, Heng Huang
Unbiased Watermark for Large Language Models. ICLR (2024)
Feihu Huang, Xidong Wu, Zhengmian Hu
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. AISTATS (2023)
Ruibo Chen, Tianyi Xiong, Yihan Wu, Guodong Liu, Zhengmian Hu, Lichang Chen, Yanshuo Chen, Chenxi Liu, Heng Huang
GPT-4 Vision on Medical Image Classification - A Case Study on COVID-19 Dataset. CoRR (2023)
Xidong Wu, Zhengmian Hu, Heng Huang
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems. AAAI (2023)
Yihan Wu, Zhengmian Hu, Hongyang Zhang, Heng Huang
DiPmark: A Stealthy, Efficient and Resilient Watermark for Large Language Models. CoRR (2023)
Xidong Wu, Zhengmian Hu, Jian Pei, Heng Huang
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining. KDD (2023)
Xidong Wu, Zhengmian Hu, Heng Huang
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems. CoRR (2023)
Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang
Federated Conditional Stochastic Optimization. NeurIPS (2023)
Zhengmian Hu, Heng Huang
Tighter Analysis for ProxSkip. ICML (2023)
Xidong Wu, Jianhui Sun, Zhengmian Hu, Aidong Zhang, Heng Huang
Solving a Class of Non-Convex Minimax Optimization in Federated Learning. CoRR (2023)
Xidong Wu, Jianhui Sun, Zhengmian Hu, Aidong Zhang, Heng Huang
Solving a Class of Non-Convex Minimax Optimization in Federated Learning. NeurIPS (2023)
Zhengmian Hu, Heng Huang
Optimization and Bayes: A Trade-off for Overparameterized Neural Networks. NeurIPS (2023)
Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, Heng Huang
Unbiased Watermark for Large Language Models. CoRR (2023)
Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang
Faster Adaptive Federated Learning. AAAI (2023)
Zhengmian Hu, Xidong Wu, Heng Huang
Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization. ICML (2023)
Zhengmian Hu, Gang Wu, Saayan Mitra, Ruiyi Zhang, Tong Sun, Heng Huang, Vishy Swaminathan
Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information. CoRR (2023)
Xidong Wu, Zhengmian Hu, Jian Pei, Heng Huang
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining. CoRR (2023)
Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang
Federated Conditional Stochastic Optimization. CoRR (2023)
Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang
Faster Adaptive Federated Learning. CoRR (2022)
Zhengmian Hu, Heng Huang
On the Random Conjugate Kernel and Neural Tangent Kernel. ICML (2021)
Huimin Wu, Zhengmian Hu, Bin Gu
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients. CoRR (2021)
Huimin Wu, Zhengmian Hu, Bin Gu
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients. AAAI (2021)
Zhengmian Hu, Feihu Huang, Heng Huang
A New Framework for Variance-Reduced Hamiltonian Monte Carlo. CoRR (2021)
Zhengmian Hu, Feihu Huang, Heng Huang
Optimal Underdamped Langevin MCMC Method. NeurIPS (2021)