Epigraphical relaxation for minimizing layered mixed norms

S Kyochi, S Ono, I Selesnick - IEEE Transactions on Signal …, 2021 - ieeexplore.ieee.org
This paper proposes an epigraphical relaxation (ERx) technique for non-proximable mixed
norm minimization. Mixed norm regularization methods play a central role in signal …

Epigraphically-Relaxed Linearly-Involved Generalized Moreau-Enhanced Model for Layered Mixed Norm Regularization

A Katsuma, S Kyochi, S Ono… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
This paper proposes an epigraphically-relaxed linearly-involved generalized Moreau-
enhanced (ER-LiGME) model for layered mixed norm regularization. Group sparse and low …

Continuation Method for Nonsmooth Model Predictive Control Using Proximal Technique

R Shima, R Moriyasu, T Kato - arXiv preprint arXiv:2409.14944, 2024 - arxiv.org
This paper presents a novel framework for the continuation method of model predictive
control based on optimal control problem with a nonsmooth regularizer. Via the proximal …

Differentiable Sparse Optimal Control

R Shima, R Moriyasu, S Kawaguchi… - IEEE Control Systems …, 2023 - ieeexplore.ieee.org
This letter develops a framework for differentiating sparse optimal control inputs with respect
to cost parameters. The difficulty lies in the non-smoothness induced by a sparsity …