13 papers · 1 filter
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 gradient method with adaptive restart for convex multiobjective optimization problems
Hao Luo, Liping Tang, Xinmin Yang
In this work, based on the continuous time approach, we propose an accelerated gradient method with adaptive residual restart for convex multiobjective optimization problems. For t…
Scaled Proximal Gradient Methods for Multiobjective Optimization: Improved Linear Convergence and Nesterov's Acceleration
Jian Chen, Liping Tang, Xinmin Yang
Over the past two decades, descent methods have received substantial attention within the multiobjective optimization field. Nonetheless, both theoretical analyses and empirical ev…
Generalized conditional gradient methods for multiobjective composite optimization problems with H{ö}lder condition
Wang Chen, Liping Tang, Xinmin Yang
In this paper, we deal with multiobjective composite optimization problems, where each objective function is a combination of smooth and possibly non-smooth functions. We first pro…
Mirror descent method for stochastic multi-objective optimization
Linxi Yang, Liping Tang, Jiahao Lv +2
Stochastic multi-objective optimization (SMOO) has recently emerged as a powerful framework for addressing machine learning problems with multiple objectives. The bias introduced b…
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…