3 papers
math.OC2026
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.OC2026
On the Resolution of Stochastic MPECs over Networks: Distributed Implicit Zeroth-Order Gradient Tracking Methods
Mohammadjavad Ebrahimi, Uday V. Shanbhag, Farzad Yousefian
The mathematical program with equilibrium constraints (MPEC) is a powerful yet challenging class of constrained optimization problems, where the constraints are characterized by a…
cs.LG2026
On Performance Guarantees for Federated Learning with Personalized Constraints
Mohammadjavad Ebrahimi, Daniel Burbano, Farzad Yousefian
Federated learning (FL) has emerged as a communication-efficient algorithmic framework for distributed learning across multiple agents. While standard FL formulations capture uncon…