4 papers
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,…
Hager-Zhang Conjugate Gradient Method for Set Optimization with Set-Valued Objective Map of Finite Cardinality
Ravi Raushan, Debdas Ghosh, Zai-Yun Peng
This work introduces a nonlinear Hager-Zhang conjugate gradient method for solving set optimization problems. The objective function under consideration is defined by a finite coll…
Nonmonotone Trust-Region Methods for Optimization of Set-Valued Mapping of Finite Cardinality
Suprova Ghosh, Debdas Ghosh, Zai-Yun Peng +1
Non-monotone trust-region methods are known to provide additional benefits for scalar and multi-objective optimization, such as enhancing the probability of convergence and improvi…
Nonlinear Conjugate Gradient Methods for Optimization of Set-Valued Mappings of Finite Cardinality
Debdas Ghosh, Ravi Raushan, Zai-Yun Peng +1
This article presents nonlinear conjugate gradient methods for finding local weakly minimal points of set-valued optimization problems under a lower set less ordering relation. The…