Cover Image

EnKSGD: A Class Of Preconditioned Black Box Optimization And Inversion Algorithms

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Irwin, Brian, Reich, Sebastian
Format:	Preprint
Published:	2023
Subjects:	Optimization and Control Numerical Analysis 65K10, 90C56, 65C35, 65C05, 62F10
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dropout Ensemble Kalman inversion for high dimensional inverse problems
by: Liu, Shuigen, et al.
Published: (2023)

Strong Global Convergence of the Consensus-Based Optimization Algorithm
by: Bonandin, Sabrina, et al.
Published: (2025)

On the Global Convergence of Particle Swarm Optimization Methods
by: Huang, Hui, et al.
Published: (2022)

Spectral conjugate gradient projection methods for large-scale monotone equations without Lipschitz continuity
by: Hamiss, Kabenge, et al.
Published: (2026)

A preconditioned difference of convex functions algorithm with extrapolation and line search
by: Zhang, Ran, et al.
Published: (2025)

Preconditioned Low-Rank Riemannian Optimization for Symmetric Positive Definite Linear Matrix Equations
by: Bioli, Ivan, et al.
Published: (2024)

Fast and robust consensus-based optimization via optimal feedback control
by: Huang, Yuyang, et al.
Published: (2024)

Swarm-based optimization with jumps: a kinetic BGK framework and convergence analysis
by: Borghi, Giacomo, et al.
Published: (2025)

A Unified Zeroth-Order Proximal Newton-Type Framework for Composite Optimization
by: Liu, Zekun, et al.
Published: (2026)

Constrained Consensus-Based Optimization and Numerical Heuristics for the Few Particle Regime
by: Beddrich, Jonas, et al.
Published: (2024)

Consensus-Based Optimization Methods Converge Globally
by: Fornasier, Massimo, et al.
Published: (2021)

Convergence of Anisotropic Consensus-Based Optimization in Mean-Field Law
by: Fornasier, Massimo, et al.
Published: (2021)

ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints
by: Krejić, Nataša, et al.
Published: (2025)

Adaptive Preconditioned Gradient Descent with Energy
by: Liu, Hailiang, et al.
Published: (2023)

Privacy-Preserving Black-Box Optimization (PBBO): Theory and the Model-Based Algorithm DFOp
by: Xie, Pengcheng
Published: (2025)

A Particle Algorithm for Mean-Field Variational Inference
by: Du, Qiang, et al.
Published: (2024)

Approximating Hessian matrices using Bayesian inference: a new approach for quasi-Newton methods in stochastic optimization
by: Carlon, Andre, et al.
Published: (2022)

Global optimality conditions for sensor placement, with extensions to binary low-rank A-optimal designs
by: Aarset, Christian
Published: (2024)

Projected Newton method for large-scale Bayesian linear inverse problems
by: Li, Haibo
Published: (2024)

Trust-region filter algorithms utilizing Hessian information for gray-box optimization
by: Hameed, Gul, et al.
Published: (2025)

FEM-based A-optimal sensor placement for heat source inversion from final time measurement
by: Aarset, Christian, et al.
Published: (2025)

Greedy Learning to Optimize with Convergence Guarantees
by: Fahy, Patrick, et al.
Published: (2024)

A particle consensus approach to solving nonconvex-nonconcave min-max problems
by: Borghi, Giacomo, et al.
Published: (2024)

Well-posedness and mean-field limit estimate of a consensus-based algorithm for min-max problems
by: Huang, Hui, et al.
Published: (2026)

SVD-Preconditioned Gradient Descent Method for Solving Nonlinear Least Squares Problems
by: Chang, Zhipeng, et al.
Published: (2026)

Stochastic momentum ADMM for nonconvex and nonsmooth optimization with application to PnP algorithm
by: Deng, Kangkang, et al.
Published: (2025)

An Optimal Interpolation Set for Model-Based Derivative-Free Optimization Methods
by: Ragonneau, Tom M., et al.
Published: (2023)

Accuracy and Relationships of Quadratic Models in Derivative-free Optimization
by: Chen, Yiwen, et al.
Published: (2026)

A Bregman ADMM for Bethe variational problem
by: Khoo, Yuehaw, et al.
Published: (2025)

Stochastic Galerkin Method and Hierarchical Preconditioning for PDE-constrained Optimization
by: Li, Zhendong, et al.
Published: (2025)

The $ω$-Condition Number: Applications to Optimal Preconditioning and Low Rank Generalized Jacobian Updating
by: Jung, Woosuk L., et al.
Published: (2023)

Strong Convergence of Relaxed Inertial Inexact Progressive Hedging Algorithm for Multi-stage Stochastic Variational Inequality Problems
by: Chen, Jiaxin, et al.
Published: (2024)

On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent
by: Laumont, Rémi, et al.
Published: (2022)

Inexact Riemannian Gradient Descent Method for Nonconvex Optimization
by: Zhou, Juan, et al.
Published: (2024)

Parameter-Free Accelerated Quasi-Newton Method for Nonconvex Optimization
by: Marumo, Naoki
Published: (2025)

An interior-point trust-region method for nonsmooth regularized bound-constrained optimization
by: Leconte, Geoffroy, et al.
Published: (2024)

Moreau envelope and proximal-point methods under the lens of high-order regularization
by: Kabgani, Alireza, et al.
Published: (2025)

Convergence of Descent Optimization Algorithms under Polyak-Łojasiewicz-Kurdyka Conditions
by: Bento, G. C., et al.
Published: (2024)

ProxiCBO: A Provably Convergent Consensus-Based Method for Composite Optimization
by: Zhang, Haoyu, et al.
Published: (2026)

Stochastic optimization over proximally smooth sets
by: Davis, Damek, et al.
Published: (2020)