Imagen de Portada

Theoretical analysis of the randomized subspace regularized Newton method for non-convex optimization

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Fuji, Terunari, Poirion, Pierre-Louis, Takeda, Akiko
Formato:	Preprint
Publicado:	2022
Materias:	Optimization and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Subspace Quasi-Newton Method with Gradient Approximation
por: Miyaishi, Taisei, et al.
Publicado: (2024)

Inexact subgradient algorithm with a non-asymptotic convergence guarantee for copositive programming problems
por: Nishijima, Mitsuhiro, et al.
Publicado: (2025)

Random-Subspace Frank--Wolfe over Strongly Convex Sets
por: Poirion, Pierre-Louis, et al.
Publicado: (2026)

Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold Method
por: Han, Andi, et al.
Publicado: (2025)

Cubic regularized subspace Newton for non-convex optimization
por: Zhao, Jim, et al.
Publicado: (2024)

Sparse Sub-gaussian Random Projections for Semidefinite Programming Relaxations
por: Guedes-Ayala, Monse, et al.
Publicado: (2024)

Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
por: Higuchi, Rei, et al.
Publicado: (2024)

Convergence analysis of a regularized Newton method with generalized regularization terms for convex optimization problems
por: Yamakawa, Yuya, et al.
Publicado: (2024)

Convergence Analysis of Randomized Subspace Normalized SGD under Heavy-Tailed Noise
por: Omiya, Gaku, et al.
Publicado: (2026)

Nonsmooth Newton methods with effective subspaces for polyhedral regularization
por: Nghia, Tran T. A., et al.
Publicado: (2025)

Fairness in Robust Unit Commitment Problem Considering Suppression of Renewable Energy
por: Toyoshima, Ichiro, et al.
Publicado: (2026)

Randomized Subspace Nesterov Accelerated Gradient
por: Omiya, Gaku, et al.
Publicado: (2026)

Zeroth-order Random Subspace Algorithm for Non-smooth Convex Optimization
por: Nozawa, Ryota, et al.
Publicado: (2024)

Convergence rates of regularized quasi-Newton methods without strong convexity
por: Wang, Shida, et al.
Publicado: (2025)

Theoretical smoothing frameworks for nonsmooth simple bilevel problems
por: Alcantara, Jan Harold, et al.
Publicado: (2024)

A primal-dual interior point trust region method for second-order stationary points of Riemannian inequality-constrained optimization problems
por: Obara, Mitsuaki, et al.
Publicado: (2025)

Computing local minimizers in polynomial optimization under genericity conditions
por: Hieu, Vu Trung, et al.
Publicado: (2023)

SSNCVX: A primal-dual semismooth Newton method for convex composite optimization problem
por: Deng, Zhanwang, et al.
Publicado: (2025)

A globalized inexact semismooth Newton method for strongly convex optimal control problems
por: Wachsmuth, Daniel
Publicado: (2025)

An inexact $q$-order regularized proximal Newton method for nonconvex composite optimization
por: Liu, Ruyu, et al.
Publicado: (2023)

Complexity and convergence analysis of a single-loop SDCAM for Lipschitz composite optimization and beyond
por: Zhang, Hao, et al.
Publicado: (2025)

Local near-quadratic convergence of Riemannian interior point methods
por: Obara, Mitsuaki, et al.
Publicado: (2025)

Douglas--Rachford for multioperator comonotone inclusions with applications to multiblock optimization
por: Alcantara, Jan Harold, et al.
Publicado: (2025)

A unified framework for inexact adaptive stepsizes in the gradient methods, the conjugate gradient methods and the quasi-Newton methods for strictly convex quadratic optimization
por: Liu, Zexian
Publicado: (2026)

Empirical and computer-aided robustness analysis of long-step and accelerated methods in smooth convex optimization
por: Vernimmen, Pierre, et al.
Publicado: (2025)

Faster stochastic cubic regularized Newton methods with momentum
por: Yang, Yiming, et al.
Publicado: (2025)

Stability of a regularized Newton method with two potentials
por: Abbas, Boushra
Publicado: (2015)

Universal heavy-ball method for nonconvex optimization under Hölder continuous Hessians
por: Marumo, Naoki, et al.
Publicado: (2023)

A fast continuous time approach for non-smooth convex optimization with time scaling and Tikhonov regularization
por: Csetnek, Robert Ernö, et al.
Publicado: (2022)

Quantum optimal transport with convex regularization
por: Caputo, Emanuele, et al.
Publicado: (2024)

Global non-asymptotic super-linear convergence rates of regularized proximal quasi-Newton methods on non-smooth composite problems
por: Wang, Shida, et al.
Publicado: (2024)

An accelerated proximal bundle method for convex optimization
por: Liao, Feng-Yi, et al.
Publicado: (2025)

Randomized gradient-free methods in convex optimization
por: Gasnikov, Alexander, et al.
Publicado: (2022)

Sequential subspace methods on Stiefel manifold optimization
por: Chen, Pengwen, et al.
Publicado: (2024)

Adaptive Newton-CG methods with global and local analysis for unconstrained optimization with Hölder continuous Hessian
por: Zeng, Ziyang, et al.
Publicado: (2026)

Exploiting higher-order derivatives in convex optimization methods
por: Kamzolov, Dmitry, et al.
Publicado: (2022)

Universal subgradient and proximal bundle methods for convex and strongly convex hybrid composite optimization
por: Guigues, Vincent, et al.
Publicado: (2024)

The robust isolated calmness of spectral norm regularized convex matrix optimization problems
por: Yin, Ziran, et al.
Publicado: (2024)

Approximate Bregman proximal gradient algorithm with variable metric Armijo--Wolfe line search
por: Fujiki, Kiwamu, et al.
Publicado: (2025)

A Simple yet Highly Accurate Prediction-Correction Algorithm for Time-Varying Optimization
por: Kamijima, Tomoya, et al.
Publicado: (2025)