Hiroyuki Sato

According to our database, Hiroyuki Sato authored at least 23 papers between 2013 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Nonlinear conjugate gradient method for vector optimization on Riemannian manifolds with retraction and vector transport.

Kangming Chen, Ellen Hidemi Fukuda, Hiroyuki Sato

Appl. Math. Comput., 2025

2023

Riemannian optimization on unit sphere with p-norm and its applications.

Hiroyuki Sato

Comput. Optim. Appl., July, 2023

Conjugate Gradient Methods for Optimization Problems on Symplectic Stiefel Manifold.

Mitsutaka Yamada, Hiroyuki Sato

IEEE Control. Syst. Lett., 2023

2022

Riemannian Conjugate Gradient Methods: General Framework and Specific Algorithms with Convergence Analyses.

Hiroyuki Sato

SIAM J. Optim., December, 2022

Topic model-based recommender systems and their applications to cold-start problems.

Mimu Kawai, Hiroyuki Sato, Takayuki Shiohama

Expert Syst. Appl., 2022

Sequential optimality conditions for nonlinear optimization on Riemannian manifolds and a globally convergent augmented Lagrangian method.

Yuya Yamakawa, Hiroyuki Sato

Comput. Optim. Appl., 2022

2021

Approximated logarithmic maps on Riemannian manifolds and their applications.

Jumpei Goto, Hiroyuki Sato

JSIAM Lett., 2021

Cayley-transform-based gradient and conjugate gradient algorithms on Grassmann manifolds.

Xiaojing Zhu, Hiroyuki Sato

Adv. Comput. Math., 2021

2020

Riemannian Optimal Identification Method for Linear Systems With Symmetric Positive-Definite Matrix.

Kazuhiro Sato, Hiroyuki Sato, Tobias Damm

IEEE Trans. Autom. Control., 2020

Riemannian conjugate gradient methods with inverse retraction.

Xiaojing Zhu, Hiroyuki Sato

Comput. Optim. Appl., 2020

2019

Cholesky QR-based retraction on the generalized Stiefel manifold.

Hiroyuki Sato, Kensuke Aihara

Comput. Optim. Appl., 2019

Riemannian Gradient-Based Online Identification Method for Linear Systems with Symmetric Positive-Definite Matrix.

Hiroyuki Sato, Kazuhiro Sato

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

Structure-Preserving H² Optimal Model Reduction Based on the Riemannian Trust-Region Method.

Kazuhiro Sato, Hiroyuki Sato

IEEE Trans. Autom. Control., 2018

2017

A matrix-free implementation of Riemannian Newton's method on the Stiefel manifold.

Kensuke Aihara, Hiroyuki Sato

Optim. Lett., 2017

Riemannian Optimal System Identification Algorithm for Linear MIMO Systems.

Hiroyuki Sato, Kazuhiro Sato

IEEE Control. Syst. Lett., 2017

Supervised-Topic-Model-Based Hybrid Filtering for Recommender Systems.

Mimu Kawai, Takayuki Shiohama, Hiroyuki Sato

Proceedings of the 5th International Conference on Applied Computing and Information Technology, 2017

2016

A Dai-Yuan-type Riemannian conjugate gradient method with the weak Wolfe conditions.

Hiroyuki Sato

Comput. Optim. Appl., 2016

A New H² optimal model reduction method based on riemannian conjugate gradient method.

Hiroyuki Sato, Kazuhiro Sato

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015

Joint singular value decomposition algorithm based on the Riemannian trust-region method.

Hiroyuki Sato

JSIAM Lett., 2015

Riemannian trust-region methods for H2 optimal model reduction.

Hiroyuki Sato, Kazuhiro Sato

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014

Riemannian conjugate gradient method for complex singular value decomposition problem.

Hiroyuki Sato

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013

A Riemannian Optimization Approach to the Matrix Singular Value Decomposition.

Hiroyuki Sato, Toshihiro Iwai

SIAM J. Optim., 2013

A complex singular value decomposition algorithm based on the Riemannian Newton method.

Hiroyuki Sato, Toshihiro Iwai

Proceedings of the 52nd IEEE Conference on Decision and Control, 2013