1 citations · 1 across the 6 of their papers we have counts for
6 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…
A Momentum-Based Variance-Reduced Algorithm for Federated Multiobjective Optimization
Yong Zhao, Chunlin You, Minh N. Dao +1
Federated learning has traditionally been formulated as a single-objective optimization problem, primarily focused on maximizing model utility. In real-world applications, however,…
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…
Memory gradient method for multiobjective optimization
Wang Chen, Xinmin Yang, Yong Zhao
In this paper, we propose a new descent method, termed as multiobjective memory gradient method, for finding Pareto critical points of a multiobjective optimization problem. The ma…
Conditional gradient method for vector optimization
Wang Chen, Xinmin Yang, Yong Zhao
In this paper, we propose a conditional gradient method for solving constrained vector optimization problems with respect to a partial order induced by a closed, convex and pointed…