Modified Fejér sequences and applications (Q1790672)

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Language	Label	Description	Also known as
English	Modified Fejér sequences and applications	scientific article

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scholarly article

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Modified Fejér sequences and applications (English)

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Lorenzo Rosasco

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Computational Optimization and Applications

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publication date

2 October 2018

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full work available at URL

https://arxiv.org/abs/1510.04641

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zbMATH Keywords

convergence of first-order methods

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proximal methods

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subgradient method

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Fejér sequence

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describes a project that uses

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MaRDI profile type

MaRDI publication profile

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Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods

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On the projected subgradient method for nonsmooth convex optimization in a Hilbert space

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Convex analysis and monotone operator theory in Hilbert spaces

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A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

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On proximal subgradient splitting method for minimizing the sum of two nonsmooth convex functions

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Scaling Techniques for $\epsilon$-Subgradient Methods

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Incremental proximal methods for large scale convex optimization

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Linear convergence of iterative soft-thresholding

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Convergence Rates in Forward--Backward Splitting

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Signal Recovery by Proximal Forward-Backward Splitting

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Proximal Splitting Methods in Signal Processing

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Stochastic Quasi-Fejér Block-Coordinate Fixed Point Iterations with Random Sweeping

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Consistent learning by composite proximal thresholding

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Variable metric quasi-Fejér monotonicity

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Convergence Rate Analysis of the Forward-Douglas-Rachford Splitting Scheme

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On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables

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On convergence rates of subgradient optimization methods

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Convergence of Approximate and Incremental Subgradient Methods for Convex Optimization

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On the convergence of conditional \(\varepsilon\)-subgradient methods for convex programs and convex-concave saddle-point problems.

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Iterative Regularization for Learning with Convex Loss Functions

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Splitting Algorithms for the Sum of Two Nonlinear Operators

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Incremental Subgradient Methods for Nondifferentiable Optimization

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Introductory lectures on convex optimization. A basic course.

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Ergodic convergence to a zero of the sum of monotone operators in Hilbert space

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Convex functions, monotone operators and differentiability.

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Stochastic forward-backward splitting for monotone inclusions

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A stochastic inertial forward–backward splitting algorithm for multivariate monotone inclusions

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A First-Order Stochastic Primal-Dual Algorithm with Correction Step

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The Variable Metric Forward-Backward Splitting Algorithm Under Mild Differentiability Assumptions

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Applications of a Splitting Algorithm to Decomposition in Convex Programming and Variational Inequalities

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Identifiers

zbMATH Open document ID

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Mathematics Subject Classification ID

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zbMATH DE Number

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10.1007/S10589-017-9962-1

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Sitelinks

Mathematics(1 entry)

mardi Publication:1790672

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