A secant-based Nesterov method for convex functions

DOI10.1007/s11590-015-0991-3zbMath1373.90100OpenAlexW2294200672MaRDI QIDQ2361131

Razak O. Alli-Oke, William Paul Heath

Publication date: 29 June 2017

Published in: Optimization Letters (Search for Journal in Brave)

Full work available at URL: https://www.research.manchester.ac.uk/portal/en/publications/a-secantbased-nesterov-method-for-convex-functions(c01e0aeb-c733-42d2-a691-1ef1181abd04).html

zbMATH Keywords

convex optimizationfast gradient methodsNesterov gradient method

Mathematics Subject Classification ID

Convex programming (90C25)

Uses Software

• ParNes
• NETLIB LP Test Set
• TFOCS

Cites Work

• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• ParNes: A rapidly convergent algorithm for accurate recovery of sparse and approximately sparse signals
• A non-monotone line search algorithm for unconstrained optimization
• On parallel complexity of nonsmooth convex optimization
• Introductory lectures on convex optimization. A basic course.
• Templates for convex cone problems with applications to sparse signal recovery
• Steepest descent with momentum for quadratic functions is a version of the conjugate gradient method
• Iteration-complexity of first-order penalty methods for convex programming
• Fine tuning Nesterov's steepest descent algorithm for differentiable convex programming
• An adaptive accelerated proximal gradient method and its homotopy continuation for sparse optimization
• Adaptive restart for accelerated gradient schemes
• An inexact line search approach using modified nonmonotone strategy for unconstrained optimization
• Benchmarking large-scale distributed convex quadratic programming algorithms
• An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control
• Two-Point Step Size Gradient Methods
• A repository of convex quadratic programming problems
• Nonmonotone Spectral Projected Gradient Methods on Convex Sets
• Fast Alternating Direction Optimization Methods
• Some Algorithms for Minimizing a Function of Several Variables
• Some methods of speeding up the convergence of iteration methods
• Surface topography using shape-from-shading
• Benchmarking optimization software with performance profiles.
• Logistic regression, AdaBoost and Bregman distances
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