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20232026
most citedA variable smoothing for Nonconvexly constrained nonsmooth optimization with application to sparse spectral clustering

2 citations · 3 across the 6 of their papers we have counts for

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6 papers

math.OC2026

Asymptotic Analysis of Gradient Mapping-type Stationarity Measure for the Sum of Nonconvex Nonsmooth Functions and Applications to Proximal Gradient-type Algorithms

Keita Kume, Isao Yamada

We propose a gradient mapping-type stationarity measure for the sum of two possibly nonsmooth nonconvex functions. Under suitable regularity assumptions, we show that Fréchet or pr…

math.OC2025

Hierarchical Variational Inequality Problem for Noncooperative Game-Theoretic Selection of Generalized Nash Equilibrium

Shota Matsuo, Keita Kume, Isao Yamada

The equilibrium selection problem in the variational Generalized Nash Equilibrium Problem (v-GNEP) has been reported as an optimization problem defined over the solution set of v-G…

math.OC2024

Hierarchical Nash Equilibrium over Variational Equilibria via Fixed-point Set Expression of Quasi-nonexpansive Operator

Shota Matsuo, Keita Kume, Isao Yamada

The equilibrium selection problem in the generalized Nash equilibrium problem (GNEP) has recently been studied as an optimization problem, defined over the set of all variational e…

math.OC2024★ 1 cited

A Proximal Variable Smoothing for Nonsmooth Minimization Involving Weakly Convex Composite with MIMO Application

Keita Kume, Isao Yamada

We propose a proximal variable smoothing algorithm for nonsmooth optimization problem with sum of three functions involving weakly convex composite function. The proposed algorithm…

math.OC2023

Piecewise Linearity of Min-Norm Solution Map of a Nonconvexly Regularized Convex Sparse Model

Yi Zhang, Isao Yamada

It is well known that the minimum -norm solution of the convex LASSO model, say , is a continuous piecewise linear function of the regularization parame…

math.OC2023★ 2 cited

A variable smoothing for Nonconvexly constrained nonsmooth optimization with application to sparse spectral clustering

Keita Kume, Isao Yamada

We propose a variable smoothing algorithm for solving nonconvexly constrained nonsmooth optimization problems. The target problem has two issues that need to be addressed: (i) the…