3 papers
math.OC2025
A Randomized Zeroth-Order Hierarchical Framework for Heterogeneous Federated Learning
Yuyang Qiu, Kibaek Kim, Farzad Yousefian
Heterogeneity in federated learning (FL) is a critical and challenging aspect that significantly impacts model performance and convergence. In this paper, we propose a novel framew…
math.OC2025
Self-tuned Regularized Federated Methods with Guarantees for Optimal Solution Selection
Mohammadjavad Ebrahimi, Yuyang Qiu, Shisheng Cui +1
We study a hierarchical federated learning (FL) problem, where clients cooperatively seek to select among multiple optimal solutions of a primary distributed learning problem, a so…
math.OC2024
Iteratively Regularized Gradient Tracking Methods for Optimal Equilibrium Seeking
Yuyang Qiu, Farzad Yousefian, Brian Zhang
In noncooperative Nash games, equilibria are often inefficient. This is exemplified by the Prisoner's Dilemma and was first provably shown in the 1980s. Since then, understanding t…