High-Performance Data, Signal and Network Optimization Group

Contact Information

6-109 Keller Hall
University of Minnesota - Twin Cities
Minneapolis, MN 55455
TEL: (612)-625-3505
Email: mhong at umn.edu

Research Interests

Our research focus on designing and analyzing large-scale optimization methods for problems arise in various domains such as data science, machine learning/AI, signal processing and networking.

Below is a list of (more or less) theoretical topics that we have worked on.

  • Design and Analysis for first-order/zeroth-order, stochastic, convex and nonconvex algorithms

  • Design and Analysis for Momentum-Based Methods

  • Distributed convex and nonconvex optimization

  • Bi-level, Min-Max optimization problems

  • Analysis of equilibrium solutions for noncooperative games

Our theoretical works are greatly empowered by their applications in various engineering fields.

  • Alignment for Large Language Models, and Diffusion Models

  • Robust (Adversarial) Machine Learning

  • Inverse Reinforcement Learning, and Structural Estimation Problems

  • Differential Privacy

  • High-dimensional machine learning

  • Distributed decision making in multi-agent heterogeneous networks

Group Photos

1500 

iangyi Graduation, May 2022

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Xiangyi Graduation Dinner, May 2022

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Group Hiking, Oct. 2022

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Group Escape Room, Dec. 2022

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Group Kayak, Sept 2023

1500 

Xinwei Graduation Dinner, Nov. 2023

1500 

Xinwei Defense, Nov. 2023