34 citations · 69 across the 15 of their papers we have counts for
5 papers · 2 filters
On the weak second-order optimality condition for nonlinear semidefinite and second-order cone programming
Ellen H. Fukuda, Gabriel Haeser, Leonardo M. Mito
Second-order necessary optimality conditions for nonlinear conic programming problems that depend on a single Lagrange multiplier are usually built under nondegeneracy and strict c…
Monotonicity for Multiobjective Accelerated Proximal Gradient Methods
Yuki Nishimura, Ellen H. Fukuda, Nobuo Yamashita
Accelerated proximal gradient methods, which are also called fast iterative shrinkage-thresholding algorithms (FISTA) are known to be efficient for many applications. Recently, Tan…
A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization
Hiroki Tanabe, Ellen H. Fukuda, Nobuo Yamashita
Convex-composite optimization, which minimizes an objective function represented by the sum of a differentiable function and a convex one, is widely used in machine learning and si…
A revised sequential quadratic semidefinite programming method for nonlinear semidefinite optimization
Kosuke Okabe, Yuya Yamakawa, Ellen H. Fukuda
In 2020, Yamakawa and Okuno proposed a stabilized sequential quadratic semidefinite programming (SQSDP) method for solving, in particular, degenerate nonlinear semidefinite optimiz…
An accelerated proximal gradient method for multiobjective optimization
Hiroki Tanabe, Ellen H. Fukuda, Nobuo Yamashita
This paper presents an accelerated proximal gradient method for multiobjective optimization, in which each objective function is the sum of a continuously differentiable, convex fu…