Proximal gradient methods for multiobjective optimization and their applications H Tanabe, EH Fukuda, N Yamashita Computational Optimization and Applications 72, 339-361, 2019 | 56 | 2019 |
Convergence rates analysis of a multiobjective proximal gradient method H Tanabe, EH Fukuda, N Yamashita Optimization Letters 17 (2), 333-350, 2023 | 28 | 2023 |
New merit functions for multiobjective optimization and their properties H Tanabe, EH Fukuda, N Yamashita Optimization, 1-38, 2023 | 22* | 2023 |
An accelerated proximal gradient method for multiobjective optimization H Tanabe, EH Fukuda, N Yamashita Computational Optimization and Applications 86 (2), 421-455, 2023 | 17 | 2023 |
A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization H Tanabe, EH Fukuda, N Yamashita arXiv preprint arXiv:2205.05262, 2022 | 7 | 2022 |
Composite Multi-Objective Optimization: Theory and Algorithms H Tanabe Kyoto University, 2022 | | 2022 |
Merit functions for multiobjective optimization and convergence rates analysis of multiobjective proximal gradient methods H Tanabe Kyoto University, 2019 | | 2019 |