Suchergebnisse - proximal-gradient algorithm*

A proximal-gradient inertial algorithm with Tikhonov regularization: strong convergence to the minimal norm solution

Autoren: László, Szilárd Csaba

Quelle: Optimization Methods and Software. 40:947-976

Schlagwörter: 34G25, 47J25, 47H05, 90C26, 90C30, 65K10, Optimization and Control (math.OC), FOS: Mathematics, Mathematics - Numerical Analysis, Numerical Analysis (math.NA), Mathematics - Optimization and Control

Zugangs-URL: http://arxiv.org/abs/2407.10350

Incremental proximal gradient algorithm using penalization strategies and fixed point techniques for solving some convex bilevel optimization problems

Autoren: A. Hanjing P. Thongpaen K. Kankam et al.

Quelle: Journal of Mathematics and Computer Science. 41:34-57

PMGT-VR: a Decentralized Proximal-gradient Algorithmic Framework with Variance Reduction

Autoren: Ye, Haishan Xiong, Wei Zhang, Tong

Quelle: IEEE Transactions on Pattern Analysis and Machine Intelligence. :1-12

Schlagwörter: FOS: Computer and information sciences, 0209 industrial biotechnology, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Optimization and Control (math.OC), 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 02 engineering and technology, Mathematics - Optimization and Control

Zugangs-URL: http://arxiv.org/abs/2012.15010

Exoplanet detection in angular and spectral differential imaging with an accelerated proximal gradient algorithm

Autoren: Nicolas Mil-Homens Cavaco Laurent Jacques Pierre-Antoine Absil

Quelle: ESANN 2025 proceesdings. :135-140

A Compressive Sensing Dual-Domain Learning Network Based on the Unfolding of the Proximal Gradient Algorithm

Quelle: Advances in Applied Mathematics. 14:280-289

Bregman Proximal Gradient Algorithm for Nonsmooth Nonconvex-Strongly Quasi-Concave Saddle Point Problems

Quelle: Advances in Applied Mathematics. 14:442-452

Structure-Preserving Accelerated Proximal Gradient Algorithm Based on l ∞ -Norm for Hankel Tensor Completion

Quelle: Advances in Applied Mathematics. 14:675-687

Majorization-Minimization Bregman Proximal Gradient Algorithms for NMF with the Kullback–Leibler Divergence

Autoren: Shota Takahashi Mirai Tanaka Shiro Ikeda

Quelle: Journal of Optimization Theory and Applications. 208

Schlagwörter: 90C26, 49M37, 15A23, Optimization and Control (math.OC), Optimization and Control, FOS: Mathematics

Zugangs-URL: http://arxiv.org/abs/2405.11185

A two-step inertial Bregman alternating structure-adapted proximal gradient descent algorithm for nonconvex and nonsmooth problems

Quelle: Journal of Nonlinear and Variational Analysis. 10

Approximate bregman proximal gradient algorithm for relatively smooth nonconvex optimization

Autoren: Shota Takahashi Akiko Takeda

Quelle: Computational Optimization and Applications. 90:227-256

Schlagwörter: 90C26, 49M37, 65K05, Optimization and Control (math.OC), 0211 other engineering and technologies, FOS: Mathematics, 02 engineering and technology, 0101 mathematics, Mathematics - Optimization and Control, 01 natural sciences

Zugangs-URL: http://arxiv.org/abs/2311.07847

A recent proximal gradient algorithm for convex minimization problem using double inertial extrapolations

Autoren: Suparat Kesornprom Papatsara Inkrong Uamporn Witthayarat et al.

Quelle: AIMS Mathematics, Vol 9, Iss 7, Pp 18841-18859 (2024)

Schlagwörter: Artificial intelligence, Inverse Problems in Mathematical Physics and Imaging, Convex Optimization, Economics, Inverse Problems, minimization problem, 0211 other engineering and technologies, Computational Mechanics, Biomedical Engineering, Geometry, 02 engineering and technology, FOS: Medical engineering, 01 natural sciences, Mathematical analysis, Quantum mechanics, Sparse Approximation, inertial extrapolation, Engineering, Compressed Sensing, Convex function, QA1-939, FOS: Mathematics, Image (mathematics), Orthogonal Matching Pursuit, 0101 mathematics, Mathematical Physics, Economic growth, Computer network, forward-backward algorithm, Minification, Physics, Mathematical optimization, Advances in Photoacoustic Imaging and Tomography, Lipschitz continuity, Rate of convergence, Theory and Applications of Compressed Sensing, Computer science, Convex optimization, Regular polygon, Algorithm, Channel (broadcasting), Physical Sciences, Convergence (economics), weak convergence, Inertial frame of reference, Mathematics

Zugangs-URL: https://doaj.org/article/3d497ac52ad64ebda166be4248739767

A preconditioned Hessian-like proximal gradient algorithm for sparse ML-DOA estimation

Autoren: Aussaguès, Thomas Ferréol, Anne Delmer, Alice et al.

Weitere Verfasser: Aussaguès, Thomas Ferréol, Anne Delmer, Alice et al.

Schlagwörter: Maximum Likelihood, Preconditioning, Sparse optimization, Second-order, [INFO] Computer Science [cs], Direction-of-Arrival estimation

Dateibeschreibung: application/pdf

Zugangs-URL: https://hal.science/hal-05241987v1

Tight Analysis of Difference-of-Convex Algorithm (DCA) Improves Convergence Rates for Proximal Gradient Descent

Autoren: Rotaru, Teodor Panagiotis, Patrinos Glineur, François et al.

Weitere Verfasser: Rotaru, Teodor Panagiotis, Patrinos Glineur, François et al.

Quelle: PMLR Proceedings of Machine Learning Research, Vol. 258, p. 4114-4122 (2025)

Zugangs-URL: https://hdl.handle.net/2078.1/300850

Adaptive accelerated proximal gradient algorithm for auto-regressive exogenous models with outliers

Autoren: Xixi Ji Jing Chen Qiang Liu et al.

Quelle: Applied Mathematical Modelling. 133:310-326

Smoothing randomized block-coordinate proximal gradient algorithms for nonsmooth nonconvex composite optimization.

Autoren: Li, Xue Bian, Wei

Quelle: Numerical Algorithms. Sep2025, Vol. 100 Issue 1, p395-424. 30p.

Schlagwörter: *NONSMOOTH optimization, *OPTIMIZATION algorithms, *EMPIRICAL research, *ASYMPTOTIC analysis, *DISCONTINUOUS functions, *STATISTICAL smoothing

Distributed Proximal-Gradient Algorithms for Nonsmooth Convex Optimization of Second-Order Multi-agent Systems

Autoren: Qing Wang Bin Xin Jie Chen

Quelle: Distributed Cooperative Control and Optimization for Multi-Agent Systems ISBN: 9789819609499

Obtaining Lower Query Complexities Through Lightweight Zeroth-Order Proximal Gradient Algorithms

Autoren: Gu, Bin Wei, Xiyuan Zhang, Hualin et al.

Quelle: Neural Computation. 36:897-935

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Optimization and Control (math.OC), FOS: Mathematics, 0211 other engineering and technologies, 02 engineering and technology, 0101 mathematics, Mathematics - Optimization and Control, 01 natural sciences, Machine Learning (cs.LG)

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38457756
http://arxiv.org/abs/2410.02559

An Improved Optimal Proximal Gradient Algorithm for Non-Blind Image Deblurring

Autoren: Wang, Qingsong Xu, Shengze Tong, Xiaojiao et al.

Index Begriffe: Computer Science - Computer Vision and Pattern Recognition, Mathematics - Optimization and Control, text

URL: http://arxiv.org/abs/2502.07602

Proximal Gradient Algorithm in the Presence of Adjoint Mismatch

Autoren: Savanier, Marion Chouzenoux, Emilie Pesquet, Jean-Christophe et al.

Weitere Verfasser: Savanier, Marion Chouzenoux, Emilie Pesquet, Jean-Christophe et al.

Quelle: 2020 European Signal Processing Conference
2020 28th European Signal Processing Conference (EUSIPCO)

Schlagwörter: Proximal gradient algorithm, adjoint mismatch, 0202 electrical engineering, electronic engineering, information engineering, fixed point methods, computed tomography, [MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC], 02 engineering and technology, image reconstruction, convergence analysis, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing

Dateibeschreibung: application/pdf

Zugangs-URL: https://hal.archives-ouvertes.fr/hal-02943659v1/file/main.pdf
https://hal.science/hal-02943659v2
https://hal.archives-ouvertes.fr/hal-02943659/document
https://dblp.uni-trier.de/db/conf/eusipco/eusipco2020.html#SavanierCPRT20
https://hal.archives-ouvertes.fr/hal-02943659v2

Accelerating Proximal Gradient-type Algorithms using Damped Anderson Acceleration with Restarts and Nesterov Initialization

Autoren: Henderson, Nicholas C. Varadhan, Ravi

Schlagwörter: FOS: Computer and information sciences, Computation, Computation (stat.CO)

Zugangs-URL: http://arxiv.org/abs/2508.12177