Zhengmian Hu

According to our database, Zhengmian Hu authored at least 17 papers between 2021 and 2023.

Collaborative distances:

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

2023

Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information.

Zhengmian Hu, Gang Wu, Saayan Mitra, Ruiyi Zhang, Tong Sun, Heng Huang, Vishy Swaminathan

CoRR, 2023

GPT-4 Vision on Medical Image Classification - A Case Study on COVID-19 Dataset.

Ruibo Chen, Tianyi Xiong, Yihan Wu, Guodong Liu, Zhengmian Hu, Lichang Chen, Yanshuo Chen, Chenxi Liu, Heng Huang

CoRR, 2023

Unbiased Watermark for Large Language Models.

Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, Heng Huang

CoRR, 2023

DiPmark: A Stealthy, Efficient and Resilient Watermark for Large Language Models.

Yihan Wu, Zhengmian Hu, Hongyang Zhang, Heng Huang

CoRR, 2023

Solving a Class of Non-Convex Minimax Optimization in Federated Learning.

Xidong Wu, Jianhui Sun, Zhengmian Hu, Aidong Zhang, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Federated Conditional Stochastic Optimization.

Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimization and Bayes: A Trade-off for Overparameterized Neural Networks.

Zhengmian Hu, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining.

Xidong Wu, Zhengmian Hu, Jian Pei, Heng Huang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization.

Zhengmian Hu, Xidong Wu, Heng Huang

Proceedings of the International Conference on Machine Learning, 2023

Tighter Analysis for ProxSkip.

Zhengmian Hu, Heng Huang

Proceedings of the International Conference on Machine Learning, 2023

AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization.

Feihu Huang, Xidong Wu, Zhengmian Hu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Faster Adaptive Federated Learning.

Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Decentralized Riemannian Algorithm for Nonconvex Minimax Problems.

Xidong Wu, Zhengmian Hu, Heng Huang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

A New Framework for Variance-Reduced Hamiltonian Monte Carlo.

Zhengmian Hu, Feihu Huang, Heng Huang

CoRR, 2021

Optimal Underdamped Langevin MCMC Method.

Zhengmian Hu, Feihu Huang, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Random Conjugate Kernel and Neural Tangent Kernel.

Zhengmian Hu, Heng Huang

Proceedings of the 38th International Conference on Machine Learning, 2021

Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients.

Huimin Wu, Zhengmian Hu, Bin Gu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021