Kyoto University - System Optimization Laboratory
※ See here for the (assit., assoc.) professor's publications.
Publications from Students and Researchers: Refereed Journal Papers
| Feb, 2024 | Shumpei Ariizumi, Yuya Yamakawa and Nobuo Yamashita | |
| Convergence properties of Levenberg-Marquardt methods with generalized regularization terms |  |
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| Applied Mathematics and Computation, vol. 463, pp. 128365, 2024 | ||
| Dec, 2023 | Kangming Chen, Ellen H. Fukuda and Nobuo Yamashita | |
| A proximal gradient method with Bregman distance in multi-objective optimization | |
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| Pacific Journal of Optimization, to appear, 2023 | ||
| Jul, 2023 | Hardik Tankaria and Nobuo Yamashita | |
| A stochastic variance reduced gradient using Barzilai-Borwein techniques as second order information | |
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| Journal of Industrial and Management Optimization, vol. 20, no. 2, pp. 525-547, 2024 | ||
| Jul, 2023 | Hiroki Tanabe, Ellen H. Fukuda and Nobuo Yamashita | |
| New merit functions for multiobjective optimization and their properties | |
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| Optimization, to appear, 2023 | ||
| Jun, 2023 | Yuya Yamakawa, Tetsuya Ikegami, Ellen H. Fukuda and Nobuo Yamashita | |
| An equivalent nonlinear optimization model with triangular low-rank factorization for semidefinite programs | |
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| Optimization Methods and Software, vol. 38, pp. 1296-1310, 2023 | ||
| May, 2023 | Hiroki Tanabe, Ellen H. Fukuda and Nobuo Yamashita | |
| An accelerated proximal gradient method for multiobjective optimization | |
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| Computational Optimization and Applications, vol. 86, pp. 421-455, 2023 | ||
| May, 2023 | Yuki Nishimura, Ellen H. Fukuda and Nobuo Yamashita | |
| Monotonicity for multiobjective accelerated proximal gradient methods | |
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| Journal of the Operations Research Society of Japan, vol. 67, no. 1, pp. 1-17, 2024 | ||
| Jan, 2023 | Kosuke Okabe, Yuya Yamakawa and Ellen H. Fukuda | |
| A revised sequential quadratic semidefinite programming method for nonlinear semidefinite optimization | |
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| Journal of Industrial and Management Optimization, vol. 19, no. 10, pp. 7777-7794, 2023 | ||
| Jan, 2023 | Atsushi Hori, Yuya Yamakawa and Nobuo Yamashita | |
| Distributionally robust expected residual minimization for stochastic variational inequality problems | |
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| Optimization Methods and Software, vol. 38, no. 4, pp. 756-780, 2023 | ||
| Nov, 2022 | Atsushi Hori and Nobuo Yamashita | |
| Two-stage distributionally robust noncooperative games: Existence of Nash equilibrium and its application to Cournot–Nash competition | |
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| Journal of Industrial and Management Optimization, vol. 19, no. 9, pp. 6430-6450, 2022 | ||
| Oct, 2022 | Shota Yamanaka and Nobuo Yamashita | |
| Duality of optimization problems with gauge functions | |
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| Optimization, vol. 73, pp. 1025-1055, 2024 | ||
| Apr, 2022 | Hiroki Tanabe, Ellen H. Fukuda and Nobuo Yamashita | |
| Convergence rates analysis of multiobjective proximal gradient methods | |
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| Optimization Letters, vol. 17, pp. 333-350, 2023 | ||
| Feb, 2022 | Hardik Tankaria, Shinji Sugimoto and Nobuo Yamashita | |
| A regularized limited memory BFGS method for large-scale unconstrained optimization and its efficient implementations | |
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| Computational Optimization and Applications, vol. 82, pp. 61-88, 2022 | ||
| Sep, 2021 | Yan Gu and Nobuo Yamashita | |
| A proximal ADMM with the Broyden family for convex optimization problems | |
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| Journal of Industrial and Management Optimization, vol. 17, no. 5, pp. 2715-2732, 2021 | ||
| Apr, 2021 | Jumpei Goto and Hiroyuki Sato | |
| Approximated logarithmic maps on Riemannian manifolds and their applications | |
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| JSIAM Letters, vol. 13, pp. 17-20, 2021 | ||
| Mar, 2021 | Yan Gu and Nobuo Yamashita | |
| An alternating direction method of multipliers with the BFGS update for structured convex quadratic optimization | |
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| Computational and Applied Mathematics, vol. 40, no. 81, 2021 | ||
| Oct, 2020 | Yan Gu and Nobuo Yamashita | |
| Alternating direction method of multipliers with variable metric indefinite proximal terms for convex optimization | |
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| Numerical Algebra, Control & Optimization, vol. 10, no. 4, pp. 487-510, 2021 | ||
| Jun, 2019 | Kanako Mita, Ellen H. Fukuda and Nobuo Yamashita | |
| Nonmonotone line searches for unconstrained multiobjective optimization problems | |
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| Journal of Global Optimization, vol. 75, pp.63-90, 2019 | ||
| Jun, 2019 | Siti Nor Habibah Binti Hassan, Tomohiro Niimi and Nobuo Yamashita | |
| Augmented Lagrangian method with alternating constraints for nonlinear optimization problems | |
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| Journal of Optimization Theory and Applications, vol. 181, pp.883-904, 2019 | ||
| Mar, 2019 | Hiroki Tanabe, Ellen H. Fukuda and Nobuo Yamashita | |
| Proximal gradient methods for multiobjective optimization and their applications | |
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| Computational Optimization and Applications, vol. 72, pp.339-361, 2019 | ||
| Feb, 2019 | Yan Gu, Xingju Cai, Deren Han, David Z. W. Wang | |
| A tri-level optimization model for a private road competition problem with traffic equilibrium constraints | |
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| European Journal of Operational Research, vol. 273, pp.190-197, 2019 | ||
| Nov, 2018 | Shota Yamanaka and Nobuo Yamashita | |
| Duality of nonconvex optimization with positively homogeneous functions | |
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| Computational Optimization and Applications, vol. 71, pp.435-456, 2018 | ||
| Nov, 2016 | Xiaoqin Hua and Nobuo Yamashita | |
| Block coordinate proximal gradient methods with variable Bregman functions for nonsmooth separable optimization | |
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| Mathematical Programming, vol. 160, pp.1-32, 2016 |
Publications from Students and Researchers: Proceedings and Technical Reports
Submitted Papers from Students and Researchers
| 2023 | Ellen H. Fukuda and Kosuke Okabe | |
| A second-order sequential optimality condition for nonlinear second-order cone programming problems | |
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| 2023 | Keigo Habara, Ellen H. Fukuda and Nobuo Yamashita | |
| Convergence analysis and acceleration of smoothing methods for solving extensive-form games | |
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| 2022 | Hiroki Tanabe, Ellen H. Fukuda and Nobuo Yamashita | |
| A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization | |
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