Positive definite matrix approximation with condition number constraint. - Mirai Tanaka; Kazuhide Nakata (Optim. Lett., 2014)

Successive Projection Method for Well-Conditioned Matrix Approximation Problems. - Mirai Tanaka; Kazuhide Nakata (IEEE Signal Process. Lett., 2014)

Estimation of Passenger Origin-Destination Matrices and Efficiency Evaluation of Public Transportation. - Mirai Tanaka; Takuya Kimata; Takeshi Arai (IIAI-AAI, 2016)

Efficient Preconditioning for Noisy Separable NMFs by Successive Projection Based Low-Rank Approximations. - Tomohiko Mizutani; Mirai Tanaka (CoRR, 2017)

Box Constrained Low-rank Matrix Approximation with Missing Values. - Manami Tatsukawa; Mirai Tanaka (ICORES, 2018)

Efficient preconditioning for noisy separable nonnegative matrix factorization problems by successive projection based low-rank approximations. - Tomohiko Mizutani; Mirai Tanaka (Mach. Learn., 2018)

Semi-flat minima and saddle points by embedding neural networks to overparameterization. - Kenji Fukumizu; Shoichiro Yamaguchi; Yoh-ichi Mototake; Mirai Tanaka (NeurIPS, 2019)

A route generation algorithm for an optimal fuel routing problem between two single ports. - Mirai Tanaka; Kazuhiro Kobayashi (Int. Trans. Oper. Res., 2019)

An Efficient Algorithm for an ℓ₁/ℓ₂ Mixed Optimal Control Problem with a Box Constraint and Parallelization. - Mitsuru Toyoda; Mirai Tanaka (IEEE Control. Syst. Lett., 2020)

Local R-linear convergence of ADMM-based algorithm for ℓ1-norm minimization with linear and box constraints. - Mitsuru Toyoda; Mirai Tanaka (Syst. Control. Lett., 2020)

A Gradient Method for Multilevel Optimization. - Ryo Sato; Mirai Tanaka; Akiko Takeda (NeurIPS, 2021)

Extension of the LP-Newton method to conic programming problems via semi-infinite representation. - Mirai Tanaka; Takayuki Okuno (Numer. Algorithms, 2021)

New Bregman proximal type algorithms for solving DC optimization problems﻿. - Shota Takahashi; Mituhiro Fukuda; Mirai Tanaka (Comput. Optim. Appl., 2022)

Efficient iterative method for SOAV minimization problem with linear equality and box constraints and its linear convergence. - Mitsuru Toyoda; Mirai Tanaka (J. Frankl. Inst., 2022)

Blind deconvolution with non-smooth regularization via Bregman proximal DCAs. - Shota Takahashi; Mirai Tanaka; Shiro Ikeda (Signal Process., 2023)

On a minimization problem of the maximum generalized eigenvalue: properties and algorithms. - Akatsuki Nishioka; Mitsuru Toyoda; Mirai Tanaka; Yoshihiro Kanno (Comput. Optim. Appl., 2025)

Proximal subgradient method for non-Lipschitz objective functions. - Mitsuru Toyoda; Mirai Tanaka (Optim. Methods Softw., 2025)

Majorization-Minimization Bregman Proximal Gradient Algorithms for NMF with the Kullback-Leibler Divergence. - Shota Takahashi; Mirai Tanaka; Shiro Ikeda (J. Optim. Theory Appl., 2026)