2024年9月24日(周二) 9:30 - 10: 30

信管学院308会议室

Kai Han received his Bachelor’s degree from the Special Class for the Gifted Young at the University of Science and Technology of China (USTC) and earned his PhD in Computer Science from the School of Computer Science and Technology, USTC. He is currently a distinguished professor at the School of Computer Science and Technology, Soochow University. Prior to 2022, he was a professor at the School of Computer Science and Technology, University of Science and Technology of China. His research interests include machine learning, big data processing, and algorithmic game theory.

Submodular Optimization: Theory and Applications

Submodularity is a property of set functions with profound theoretical implications and far-reaching applications. In recent years, submodular optimization problems have garnered significant interest across diverse domains, including machine learning, big data processing, and algorithmic game theory. This presentation will delve into our recent studies on pivotal submodular optimization problems, such as submodular maximization under matroid, k-system, and knapsack constraints, as well as budget-feasible mechanism design with submodular valuations. We will then explore several applications of submodular optimization, including adaptive influence maximization, incentivized social advertising, and pricing for crowdsourcing. Finally, we will discuss some future research opportunities and challenges related to submodular optimization.