Riemannian stochastic variance reduced gradient algorithm with retraction and vector transport H Sato, H Kasai, B Mishra
SIAM Journal on Optimization 29 (2), 1444-1472, 2019
145 * 2019 A new, globally convergent Riemannian conjugate gradient method H Sato, T Iwai
Optimization 64 (4), 1011-1031, 2015
131 2015 Benchmarking principal component analysis for large-scale single-cell RNA-sequencing K Tsuyuzaki, H Sato, K Sato, I Nikaido
Genome Biology 21 (1), 9, 2020
93 2020 A Dai–Yuan-type Riemannian conjugate gradient method with the weak Wolfe conditions H Sato
Computational Optimization and Applications 64 (1), 101-118, 2016
74 2016 Riemannian Optimization and Its Applications H Sato
Springer, 2021
63 2021 A Riemannian optimization approach to the matrix singular value decomposition H Sato, T Iwai
SIAM Journal on Optimization 23 (1), 188-212, 2013
58 2013 Riemannian stochastic recursive gradient algorithm H Kasai, H Sato, B Mishra
International Conference on Machine Learning, 2516-2524, 2018
51 2018 Riemannian conjugate gradient methods: General framework and specific algorithms with convergence analyses H Sato
SIAM Journal on Optimization 32 (4), 2690-2717, 2022
39 2022 Structure-Preserving Optimal Model Reduction Based on the Riemannian Trust-Region Method K Sato, H Sato
IEEE Transactions on Automatic Control 63 (2), 505-512, 2017
35 2017 Riemannian conjugate gradient methods with inverse retraction X Zhu, H Sato
Computational Optimization and Applications 77 (3), 779-810, 2020
28 2020 Riemannian trust-region methods for H2 optimal model reduction H Sato, K Sato
2015 54th IEEE Conference on Decision and Control (CDC), 4648-4655, 2015
28 2015 Riemannian Newton-type methods for joint diagonalization on the Stiefel manifold with application to independent component analysis H Sato
Optimization 66 (12), 2211-2231, 2017
27 * 2017 Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis H Kasai, H Sato, B Mishra
International Conference on Artificial Intelligence and Statistics, 269-278, 2018
24 2018 Optimization algorithms on the Grassmann manifold with application to matrix eigenvalue problems H Sato, T Iwai
Japan Journal of Industrial and Applied Mathematics 31 (2), 355-400, 2014
23 2014 Cholesky QR-based retraction on the generalized Stiefel manifold H Sato, K Aihara
Computational Optimization and Applications 72 (2), 293-308, 2019
22 2019 Topic model-based recommender systems and their applications to cold-start problems M Kawai, H Sato, T Shiohama
Expert Systems with Applications 202, 117129, 2022
17 2022 A matrix-free implementation of Riemannian Newton’s method on the Stiefel manifold K Aihara, H Sato
Optimization Letters 11 (8), 1729-1741, 2017
17 2017 Joint singular value decomposition algorithm based on the Riemannian trust-region method H Sato
JSIAM Letters 7, 13-16, 2015
13 2015 Riemannian conjugate gradient method for complex singular value decomposition problem H Sato
53rd IEEE Conference on Decision and Control, 5849-5854, 2014
13 2014 A complex singular value decomposition algorithm based on the Riemannian Newton method H Sato, T Iwai
52nd IEEE Conference on Decision and Control, 2972-2978, 2013
13 2013