Hong, Mingyi

Learning to Optimize: Training Deep Neural Networks for Interference Management

Sun, H., Chen, X., Shi, Q., Hong, M., Fu, X., & Sidiropoulos, N. D. (2018) · IEEE Transactions on Signal Processing

Advanced MIMO Systems OptimizationAdvanced Wireless Network Optimization

Cited by 874

Multi-Agent Distributed Optimization via Inexact Consensus ADMM

Chang, T.-H., Hong, M., & Wang, X. (2015) · IEEE Transactions on Signal Processing

Distributed Control Multi-Agent SystemsSparse and Compressive Sensing Techniques

Cited by 444

Learning to optimize: Training deep neural networks for wireless resource management

Sun, H., Chen, X., Shi, Q., Hong, M., Fu, X., & Sidiropoulos, N. D. (2017) · 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

Advanced Wireless Network OptimizationAdvanced MIMO Systems Optimization

Cited by 308

Learning to Continuously Optimize Wireless Resource in Episodically Dynamic Environment

Sun, H., Pu, W., Zhu, M., Fu, X., Chang, T.-H., & Hong, M. (2021) · ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Domain Adaptation and Few-Shot LearningAdvanced Wireless Network Optimization

Cited by 21

Stochastic proximal gradient consensus over time-varying networks

Hong, M., & Chang, T.-H. (2016) · 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Distributed Control Multi-Agent SystemsStochastic Gradient Optimization Techniques

Cited by 6

Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs

Zhao, S., Hong, M., Liu, Y., Hazarika, D., & Lin, K. (2025) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 3