9 papers · 1 filter
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…
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…
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…