7 papers
Preconditioned Proximal Gradient Methods with Conjugate Momentum: A Subspace Perspective
Jian Chen, Xinmin Yang
In this paper, we propose a descent method for composite optimization problems with linear operators. Specifically, we first design a structure-exploiting preconditioner tailored t…
Second-order Methods for Multiobjective Composite Optimization: Preconditioning Strategies, Subspace Variants and Inexact Solutions
Jian Chen, Xinmin Yang
Multiobjective composite optimization problems arise in sparse regularization, constrained multiobjective models, and multi-task learning, but their numerical solution remains chal…
Level proximal subdifferential, variational convexity, and pointwise quadratic approximation
Honglin Luo, Xianfu Wang, Ziyuan Wang +1
Level proximal subdifferential was introduced by Rockafellar recently for studying proximal mappings of possibly nonconvex functions. In this paper a systematic study of level prox…
First-order Methods for Unconstrained Vector Optimization Problems: A Unified Majorization-Minimization Perspective
Jian Chen, Jingjie Liu, Liping Tang +1
In this paper, we develop a unified majorization-minimization scheme and convergence analysis with first-order surrogate functions for unconstrained vector optimization problems (V…
Barzilai-Borwein Diagonal Quasi-Newton Method for Nonconvex Multiobjective Optimization Problems
Hua Liu, Zhuoxin Fan, Liping Tang +1
This paper addresses the challenge of developing efficient algorithms for large-scale nonconvex multiobjective optimization problems (MOPs). While quasi-Newton methods are effectiv…
An accelerated primal-dual flow for linearly constrained multiobjective optimization
Hao Luo, Qiaoyuan Shu, Xinmin Yang
In this paper, we propose a continuous-time primal-dual approach for linearly constrained multiobjective optimization problems. A novel dynamical model, called accelerated multiobj…