3 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
On the Oracle Complexity of a Riemannian Inexact Augmented Lagrangian Method for Riemannian Nonsmooth Composite Problems
Meng Xu, Bo Jiang, Ya-Feng Liu +1
In this paper, we establish for the first time the oracle complexity of a Riemannian inexact augmented Lagrangian (RiAL) method with the classical dual update for solving a class o…
A Riemannian Alternating Descent Ascent Algorithmic Framework for Nonconvex-Linear Minimax Problems on Riemannian Manifolds
Meng Xu, Bo Jiang, Ya-Feng Liu +1
In this paper, we consider a class of nonconvex-linear minimax problems on Riemannian manifolds, which find wide applications in machine learning and signal processing. For solving…
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
Jiaojiao Zhang, Jiang Hu, Anthony Man-Cho So +1
Many machine learning tasks, such as principal component analysis and low-rank matrix completion, give rise to manifold optimization problems. Although there is a large body of wor…
Extreme Point Pursuit -- Part II: Further Error Bound Analysis and Applications
Junbin Liu, Ya Liu, Wing-Kin Ma +2
In the first part of this study, a convex-constrained penalized formulation was studied for a class of constant modulus (CM) problems. In particular, the error bound techniques wer…
A Survey of Recent Advances in Optimization Methods for Wireless Communications
Ya-Feng Liu, Tsung-Hui Chang, Mingyi Hong +4
Mathematical optimization is now widely regarded as an indispensable modeling and solution tool for the design of wireless communications systems. While optimization has played a s…