2023/11/16 by Khanh-Hung Giang-Tran, Giang-Tran, Khanh-Hung, Nam Ho-Nguyen +3 · 7 citations
Computer Science · Decision Sciences · Mathematics · #90C06 #90C25 #90C30 #Advanced Optimization Algorithms Research #FOS: Mathematics #Optimization and Control (math.OC) #Optimization and Variational Analysis #Risk and Portfolio Optimization
paper · pdf · doi:10.48550/arxiv.2311.09738
openalex publication_date 2023/11/16 · openalex created_date 2023/11/18 · openalex updated_date 2026/07/28
When faced with multiple minima of an "inner-level" convex optimization problem, the convex bilevel optimization problem selects an optimal solution which also minimizes an auxiliary "outer-level" convex objective of interest. Bilevel optimization requires a different approach compared to single-level optimization problems since the set of minimizers for the inner-level objective is not given explicitly. In this paper, we propose a new projection-free method for convex bilevel optimization which require only a linear optimization oracle over the base domain. We establish O(t-1/2) convergence rate guarantees for our method in terms of both inner- and outer-level objectives, and demonstrate how additional assumptions such as quadratic growth and strong convexity result in accelerated rates of up to O(t-1) and O(t-2/3) for inner- and outer-levels respectively. Lastly, we conduct a numerical study to demonstrate the performance of our method.