Studies on Optimization Methods for Nonlinear Semidefinite Programming Problems. - Yuya Yamakawa (2015)

A stabilized sequential quadratic semidefinite programming method for degenerate nonlinear semidefinite programs. - Yuya Yamakawa; Takayuki Okuno (Comput. Optim. 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)

Distributionally robust expected residual minimization for stochastic variational inequality problems. - Atsushi Hori; Yuya Yamakawa; Nobuo Yamashita (Optim. Methods Softw., 2023)

An equivalent nonlinear optimization model with triangular low-rank factorization for semidefinite programs. - Yuya Yamakawa; Tetsuya Ikegami; Ellen H. Fukuda; Nobuo Yamashita (Optim. Methods Softw., 2023)

Convergence properties of Levenberg-Marquardt methods with generalized regularization terms. - Shumpei Ariizumi; Yuya Yamakawa; Nobuo Yamashita (Appl. Math. Comput., 2024)

Convergence analysis of a regularized Newton method with generalized regularization terms for unconstrained convex optimization problems. - Yuya Yamakawa; Nobuo Yamashita (Appl. Math. Comput., 2025)