1 citations · 1 across the 18 of their papers we have counts for
18 papers
A Tight Surrogate-Based Adaptive Step Size for the Multiobjective Conditional Gradient Method
Wang Chen, Yong Zhao, Liping Tang +1
The multiobjective conditional gradient (MCondG) method is an effective descent-type algorithm for solving constrained multiobjective optimization problems. In this algorithm, the…
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…
A Subspace Minimization Barzilai-Borwein Method for Multiobjective Optimization Problems
Jian Chen, Liping Tang. Xinmin Yang
Nonlinear conjugate gradient methods have recently garnered significant attention within the multiobjective optimization community. These methods aim to maintain consistency in con…
On the convergence of conditional gradient method for unbounded multiobjective optimization problems
Wang Chen, Yong Zhao, Liping Tang +1
This paper focuses on developing a conditional gradient algorithm for multiobjective optimization problems with an unbounded feasible region. We employ the concept of recession con…
Conjugate gradient methods without line search for multiobjective optimization
Wang Chen, Yong Zhao, Liping Tang +1
This paper addresses unconstrained multiobjective optimization problems where two or more continuously differentiable functions have to be minimized. We delve into the conjugate gr…
Improvements to steepest descent method for multi-objective optimization
Wang Chen, Liping Tang, Xinmin Yang
In this paper, we propose a simple yet efficient strategy for improving the multi-objective steepest descent method proposed by Fliege and Svaiter (Math Methods Oper Res, 2000, 3:…
Learning to optimize by multi-gradient for multi-objective optimization
Linxi Yang, Xinmin Yang, Liping Tang
The development of artificial intelligence (AI) for science has led to the emergence of learning-based research paradigms, necessitating a compelling reevaluation of the design of…
Barzilai-Borwein Descent Methods for Multiobjective Optimization Problems with Variable Trade-off Metrics
Jian Chen, Liping Tang, Xinmin Yang
The imbalances and conditioning of the objective functions influence the performance of first-order methods for multiobjective optimization problems (MOPs). The latter is related t…
On the Convergence of Newton-type Proximal Gradient Method for Multiobjective Optimization Problems
Jian Chen, Xiaoxue Jiang, Liping Tang +1
In a recent study, Ansary (Optim Methods Softw 38(3):570-590,2023) proposed a Newton-type proximal gradient method for nonlinear multiobjective optimization problems (NPGMO). Howev…
A Modification Piecewise Convexification Method for Box-Constrained Non-Convex Optimization Programs
Qiao Zhu, Liping Tang, Xinmin Yang
This paper presents a piecewise convexification method to approximate the whole approximate optimal solution set of non-convex optimization problems with box constraints. In the pr…
A Piecewise Convexification Method for Non-Convex Multi-Objective Optimization Programs with Box Constraints
Q. Zhu, L. P. Tang, X. M. Yang
This paper presents a piecewise convexification method for solving non-convex multi-objective optimization problems with box constraints. Based on the ideas of the -based Branch…
Convergence rates analysis of Interior Bregman Gradient Method for Vector Optimization Problems
Jian Chen, Liping Tang, Xinmin Yang
In recent years, by using Bregman distance, the Lipschitz gradient continuity and strong convexity were lifted and replaced by relative smoothness and relative strong convexity. Un…
A Barzilai-Borwein Descent Method for Multiobjective Optimization Problems
Jian Chen, Liping Tang, Xinmin Yang
The steepest descent method proposed by Fliege et al. motivates the research on descent methods for multiobjective optimization, which has received increasing attention in recent y…