1 citations · 1 across the 2 of their papers we have counts for
2 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…
cs.LG2024★ 1 cited
Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays
Charikleia Iakovidou, Kibaek Kim
Federated learning (FL) was recently proposed to securely train models with data held over multiple locations (``clients'') under the coordination of a central server. Prolonged tr…