First-Order Methods for Bilevel Optimization
Abstract: Bilevel optimization, also known as two-level optimization, is an important branch within mathematical optimization. It has found applications across various domains, including economics, logistics, supply chain, transportation, engineering design, and machine learning. In this talk, we will present first-order methods for solving a class of bilevel optimization problems using either single or sequential minimax optimization schemes. We will discuss the first-order operation complexity of these methods and present preliminary numerical results to illustrate their performance.
This is joint work with Sanyou Mei (University of Minnesota).
Biography: Zhaosong Lu is a Full Professor in the Department of Industrial and Systems Engineering at the University of Minnesota. He received his Ph.D. in Operations Research from Georgia Institute of Technology. His research focuses on the theory and algorithms for continuous optimization, with applications in data science and machine learning. He has published extensively in top-tier journals, including Mathematical Programming, Mathematics of Operations Research, SIAM Journal on Optimization, SIAM Journal on Numerical Analysis, SIAM Journal on Scientific Computing, and SIAM Journal on Matrix Analysis and Applications. His research has been supported by AFOSR, NSERC, NSF, and ONR. In addition, he has served as an Associate Editor for SIAM Journal on Optimization, Computational Optimization and Applications, and Big Data and Information Analytics.