报告题目 (Title)：A Single-Loop Algorithm for Decentralized Bilevel Optimization（求解去中心化双层优化问题的单循环算法）
报告人 (Speaker)：杨俊锋 教授（南京大学）
报告时间 (Time)：2025年07月1日(周二) 8：00
报告地点 (Place)：校本部GJ303
邀请人(Inviter)：周安娃
报告摘要： Bilevel optimization (BO) has gained significant attention in recent years due to its broad applications in machine learning. In this talk, we focus on decentralized BO and proposes a novel single-loop algorithm for solving it with a strongly convex lower-level problem. Our approach is a fully single-loop method that approximates the hypergradient using only two matrix-vector multiplications per iteration. Our algorithm does not require any gradient heterogeneity assumption and achieves the best-known convergence rate for BO algorithms. We also present experimental results on hyperparameter optimization problems using both synthetic and MNIST datasets, which demonstrate the efficiency of our proposed algorithm.