Mathematical programming, ISSN 1436-4646, 2018, Volume 174, Issue 1-2, pp. 391 - 432

We study the behavior of the trajectories of a second-order differential equation with vanishing damping, governed by the Yosida regularization of a maximally monotone operator with time-varying index...

Lyapunov analysis | Time-dependent viscosity | 65K05 | Theoretical, Mathematical and Computational Physics | Asymptotic stabilization | Mathematics | Yosida regularization | 37N40 | Mathematical Methods in Physics | 49M30 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Damped inertial dynamics | Maximally monotone operators | Vanishing viscosity | Large step proximal method | 65K10 | Combinatorics | 90B50 | 46N10 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Analysis | Algorithms | Differential equations | Operators | Parameters | Trajectory analysis | Regularization | Convergence | Finite difference method | Optimization and Control

Lyapunov analysis | Time-dependent viscosity | 65K05 | Theoretical, Mathematical and Computational Physics | Asymptotic stabilization | Mathematics | Yosida regularization | 37N40 | Mathematical Methods in Physics | 49M30 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Damped inertial dynamics | Maximally monotone operators | Vanishing viscosity | Large step proximal method | 65K10 | Combinatorics | 90B50 | 46N10 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Analysis | Algorithms | Differential equations | Operators | Parameters | Trajectory analysis | Regularization | Convergence | Finite difference method | Optimization and Control

Journal Article

Journal of optimization theory and applications, ISSN 1573-2878, 2019, Volume 181, Issue 3, pp. 709 - 726

.... In this work, we generalize the scheme so that it can be used to compute the resolvent of the sum of two maximally monotone operators...

Maximally monotone operator | Douglas–Rachford algorithm | Resolvent | Splitting method | Averaged alternating modified reflections algorithm | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | 65K05 | Douglas-Rachford algorithm | 47H05 | 47J25 | 47N10 | Computational geometry | Operators | Splitting | Hilbert space | Algorithms | Convexity

Maximally monotone operator | Douglas–Rachford algorithm | Resolvent | Splitting method | Averaged alternating modified reflections algorithm | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | 65K05 | Douglas-Rachford algorithm | 47H05 | 47J25 | 47N10 | Computational geometry | Operators | Splitting | Hilbert space | Algorithms | Convexity

Journal Article

Numerical algorithms, ISSN 1572-9265, 2015, Volume 71, Issue 3, pp. 519 - 540

We introduce and investigate the convergence properties of an inertial forward-backward-forward splitting algorithm for approaching the set of zeros of the sum of a maximally monotone operator...

Primal-dual algorithm | 65K05 | Subdifferential | Numeric Computing | Theory of Computation | Inertial splitting algorithm | Maximally monotone operator | Algorithms | Algebra | Resolvent | Convex optimization | 90C25 | Numerical Analysis | Computer Science | 47H05 | MATHEMATICS, APPLIED | PROXIMAL POINT ALGORITHM | COMPOSITE | CONVERGENCE | MAPPINGS | OPTIMIZATION | OPERATORS | Operators | Splitting | Image processing | Inertial | Inclusions | Optimization | Convergence

Primal-dual algorithm | 65K05 | Subdifferential | Numeric Computing | Theory of Computation | Inertial splitting algorithm | Maximally monotone operator | Algorithms | Algebra | Resolvent | Convex optimization | 90C25 | Numerical Analysis | Computer Science | 47H05 | MATHEMATICS, APPLIED | PROXIMAL POINT ALGORITHM | COMPOSITE | CONVERGENCE | MAPPINGS | OPTIMIZATION | OPERATORS | Operators | Splitting | Image processing | Inertial | Inclusions | Optimization | Convergence

Journal Article

Optimization, ISSN 1029-4945, 2018, Volume 68, Issue 10, pp. 1855 - 1880

We investigate a forward-backward splitting algorithm of penalty type with inertial effects for finding the zeros of the sum of a maximally monotone operator and a cocoercive one and the convex normal...

Maximally monotone operator | forward-backward splitting algorithm | convex bilevel optimization | Fitzpatrick function | 65K05 | forward–backward splitting algorithm | 90C25 | 47H05 | Operators (mathematics) | Algorithms | Inclusions | Convergence | Ergodic processes

Maximally monotone operator | forward-backward splitting algorithm | convex bilevel optimization | Fitzpatrick function | 65K05 | forward–backward splitting algorithm | 90C25 | 47H05 | Operators (mathematics) | Algorithms | Inclusions | Convergence | Ergodic processes

Journal Article

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Firmly Nonexpansive Mappings and Maximally Monotone Operators: Correspondence and Duality

Set-valued and variational analysis, ISSN 1877-0541, 2011, Volume 20, Issue 1, pp. 131 - 153

The notion of a firmly nonexpansive mapping is central in fixed point theory because of attractive convergence properties for iterates and the correspondence with maximally monotone operators due to Minty...

Banach contraction | 52A41 | Proximal map | Subdifferential operator | Mathematics | Nonexpansive mapping | Geometry | Maximally monotone operator | Rectangular | Resolvent | Secondary 26B25 | Primary 47H05 | 90C25 | Analysis | Firmly nonexpansive mapping | 47H09 | Convex function | Hilbert space | Legendre function | Paramonotone | Fixed point | MATHEMATICS, APPLIED | FITZPATRICK FUNCTIONS | EXTENSION | NONLINEAR OPERATORS | CONVERGENCE

Banach contraction | 52A41 | Proximal map | Subdifferential operator | Mathematics | Nonexpansive mapping | Geometry | Maximally monotone operator | Rectangular | Resolvent | Secondary 26B25 | Primary 47H05 | 90C25 | Analysis | Firmly nonexpansive mapping | 47H09 | Convex function | Hilbert space | Legendre function | Paramonotone | Fixed point | MATHEMATICS, APPLIED | FITZPATRICK FUNCTIONS | EXTENSION | NONLINEAR OPERATORS | CONVERGENCE

Journal Article

Set-Valued and Variational Analysis, ISSN 1877-0533, 6/2018, Volume 26, Issue 2, pp. 369 - 384

Given two point to set operators, one of which is maximally monotone, we introduce a new distance in their graphs...

65K15 | Probability Theory and Stochastic Processes | Mathematics | Banach spaces | 47J20 | Analysis | 49J40 | 90C33 | Maximally monotone operators | Representable operators | 65K10 | Convex functions | 49M37 | Fitzpatrick functions | 47H05 | 47H14 | Bregman distances | Variational inequalities | 47H04 | MATHEMATICS, APPLIED | ENLARGEMENTS | FAMILY

65K15 | Probability Theory and Stochastic Processes | Mathematics | Banach spaces | 47J20 | Analysis | 49J40 | 90C33 | Maximally monotone operators | Representable operators | 65K10 | Convex functions | 49M37 | Fitzpatrick functions | 47H05 | 47H14 | Bregman distances | Variational inequalities | 47H04 | MATHEMATICS, APPLIED | ENLARGEMENTS | FAMILY

Journal Article

Journal of optimization theory and applications, ISSN 1573-2878, 2012, Volume 157, Issue 1, pp. 1 - 24

In this paper, we consider the structure of maximally monotone operators in Banach space whose domains have nonempty interior and we present new and explicit structure formulas for such operators...

Maximally monotone operator | Property (Q) | Calculus of Variations and Optimal Control; Optimization | Norm-weak ∗ graph closedness | Operations Research/Decision Theory | Mathematics | Theory of Computation | Local boundedness | Monotone operator | Applications of Mathematics | Engineering, general | Optimization | graph closedness | Norm-weak | Property (Q) | MATHEMATICS, APPLIED | DOMAIN | DIFFERENTIABILITY | SUMS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Norm-weak graph closedness | SETS | SMOOTH BANACH-SPACES | MAPPINGS | SUBDIFFERENTIALS | Studies | Graph theory | Banach spaces | Analysis | Operators | Continuity | Banach space | Proving | Constraining

Maximally monotone operator | Property (Q) | Calculus of Variations and Optimal Control; Optimization | Norm-weak ∗ graph closedness | Operations Research/Decision Theory | Mathematics | Theory of Computation | Local boundedness | Monotone operator | Applications of Mathematics | Engineering, general | Optimization | graph closedness | Norm-weak | Property (Q) | MATHEMATICS, APPLIED | DOMAIN | DIFFERENTIABILITY | SUMS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Norm-weak graph closedness | SETS | SMOOTH BANACH-SPACES | MAPPINGS | SUBDIFFERENTIALS | Studies | Graph theory | Banach spaces | Analysis | Operators | Continuity | Banach space | Proving | Constraining

Journal Article

Nonlinear Analysis, ISSN 0362-546X, 08/2013, Volume 87, pp. 69 - 82

Maximally monotone operators play important roles in optimization, variational analysis and differential equations...

Maximally monotone operator | Baire category | Resolvent | Weakly contractive mapping | Reflected resolvent | Asymptotic regularity | Graphical convergence | Super-regularity | Zeros of monotone operator | Nonexpansive mapping | Fixed point | MATHEMATICS, APPLIED | FITZPATRICK FUNCTIONS | PROXIMAL POINT ALGORITHM | CONTRACTIONS | MATHEMATICS | NONEXPANSIVE OPERATORS | MANN ITERATIONS | BANACH-SPACES | MAPPINGS | CONVERGENCE | DUALITY | FIXED-POINTS | Categories

Maximally monotone operator | Baire category | Resolvent | Weakly contractive mapping | Reflected resolvent | Asymptotic regularity | Graphical convergence | Super-regularity | Zeros of monotone operator | Nonexpansive mapping | Fixed point | MATHEMATICS, APPLIED | FITZPATRICK FUNCTIONS | PROXIMAL POINT ALGORITHM | CONTRACTIONS | MATHEMATICS | NONEXPANSIVE OPERATORS | MANN ITERATIONS | BANACH-SPACES | MAPPINGS | CONVERGENCE | DUALITY | FIXED-POINTS | Categories

Journal Article

Set-Valued and Variational Analysis, ISSN 1877-0533, 6/2012, Volume 20, Issue 2, pp. 155 - 167

The most important open problem in Monotone Operator Theory concerns the maximal monotonicity of the sum of two maximally monotone operators provided...

Constraint qualification | Convex set | Fitzpatrick function | Subdifferential operator | Set-valued operator | Mathematics | Monotone operator | Linear relation | Multifunction | Rockafellar’s sum theorem | Geometry | Maximally monotone operator | Secondary 47B65 | Monotone operator of type (FPV) | 90C25 | Analysis | Normal cone operator | Convex function | 47H05 | 47N10 | Primary 47A06 | Rockafellar's sum theorem | MATHEMATICS, APPLIED | THEOREM | FITZPATRICK FUNCTIONS | OPERATORS

Constraint qualification | Convex set | Fitzpatrick function | Subdifferential operator | Set-valued operator | Mathematics | Monotone operator | Linear relation | Multifunction | Rockafellar’s sum theorem | Geometry | Maximally monotone operator | Secondary 47B65 | Monotone operator of type (FPV) | 90C25 | Analysis | Normal cone operator | Convex function | 47H05 | 47N10 | Primary 47A06 | Rockafellar's sum theorem | MATHEMATICS, APPLIED | THEOREM | FITZPATRICK FUNCTIONS | OPERATORS

Journal Article

Journal of the Australian Mathematical Society (2001), ISSN 1446-7887, 08/2014, Volume 97, Issue 1, pp. 1 - 26

The most important open problem in monotone operator theory concerns the maximal monotonicity of the sum of two maximally monotone operators provided that the classical...

convex set | Fitzpatrick function | operator of type (FPV) | sum problem | convex function | constraint qualification | linear relation | maximally monotone operator | monotone operator | MATHEMATICS | DOMAIN | CONVEX-SETS | Mathematics - Functional Analysis

convex set | Fitzpatrick function | operator of type (FPV) | sum problem | convex function | constraint qualification | linear relation | maximally monotone operator | monotone operator | MATHEMATICS | DOMAIN | CONVEX-SETS | Mathematics - Functional Analysis

Journal Article

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Every maximally monotone operator of Fitzpatrick–Phelps type is actually of dense type

Optimization Letters, ISSN 1862-4472, 12/2012, Volume 6, Issue 8, pp. 1875 - 1881

We show that every maximally monotone operator of Fitzpatrick–Phelps type defined on a real Banach space must be of dense type...

Operator of type (NI) | Fitzpatrick function | Set-valued operator | Mathematics | Monotone operator | Multifunction | Operator of type (FP) | Optimization | Maximally monotone operator | Computational Intelligence | Operations Research/Decision Theory | Numerical and Computational Physics | Operator of type (D) | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | BANACH-SPACES

Operator of type (NI) | Fitzpatrick function | Set-valued operator | Mathematics | Monotone operator | Multifunction | Operator of type (FP) | Optimization | Maximally monotone operator | Computational Intelligence | Operations Research/Decision Theory | Numerical and Computational Physics | Operator of type (D) | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | BANACH-SPACES

Journal Article

Optimization Letters, ISSN 1862-4472, 1/2014, Volume 8, Issue 1, pp. 237 - 246

We provide a concise analysis about what is known regarding when the closure of the domain of a maximally monotone operator on an arbitrary real Banach space is convex...

Fitzpatrick function | Set-valued operator | 47B65 | Mathematics | Monotone operator | Optimization | Maximally monotone operator | Computational Intelligence | Secondary 26B25 | Primary 47H05 | Nearly convex set | 47A05 | Operations Research/Decision Theory | Numerical and Computational Physics | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MULTIFUNCTIONS | SUM

Fitzpatrick function | Set-valued operator | 47B65 | Mathematics | Monotone operator | Optimization | Maximally monotone operator | Computational Intelligence | Secondary 26B25 | Primary 47H05 | Nearly convex set | 47A05 | Operations Research/Decision Theory | Numerical and Computational Physics | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MULTIFUNCTIONS | SUM

Journal Article

Numerical functional analysis and optimization, ISSN 1532-2467, 2015, Volume 36, Issue 8, pp. 951 - 963

... of a maximally monotone operator in real Hilbert spaces. The convergence analysis relies on extended...

Enlargement of a maximally monotone operator | Maximally monotone operator | Resolvent | Hybrid proximal point algorithm | Inertial splitting algorithm | MATHEMATICS, APPLIED | MAXIMAL MONOTONE-OPERATORS | CONVERGENCE | ENLARGEMENT | POINT ALGORITHM | Operators (mathematics) | Algorithms | Mathematical models | Functional analysis | Inertial | Iterative methods | Optimization | Convergence

Enlargement of a maximally monotone operator | Maximally monotone operator | Resolvent | Hybrid proximal point algorithm | Inertial splitting algorithm | MATHEMATICS, APPLIED | MAXIMAL MONOTONE-OPERATORS | CONVERGENCE | ENLARGEMENT | POINT ALGORITHM | Operators (mathematics) | Algorithms | Mathematical models | Functional analysis | Inertial | Iterative methods | Optimization | Convergence

Journal Article

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The Douglas--Rachford Algorithm for Two (Not Necessarily Intersecting) Affine Subspaces

SIAM journal on optimization, ISSN 1095-7189, 2016, Volume 26, Issue 2, pp. 968 - 985

The Douglas-Rachford algorithm is a classical and very successful splitting method for finding the zeros of the sums of monotone operators...

Maximally monotone operator | Affine subspace | Projection operator | Linear convergence | Normal problem | Douglas-Rachford splitting operator | Generalized solution | Attouch-Théra duality | Firmly nonexpansive mapping | Normal cone operator | Fixed point | MATHEMATICS, APPLIED | affine subspace | normal cone operator | FEASIBILITY | projection operator | Attouch-Thera duality | SUM | maximally monotone operator | firmly nonexpansive mapping | fixed point | linear convergence | CONVERGENCE | normal problem | ALTERNATING PROJECTIONS | generalized solution | MONOTONE-OPERATORS

Maximally monotone operator | Affine subspace | Projection operator | Linear convergence | Normal problem | Douglas-Rachford splitting operator | Generalized solution | Attouch-Théra duality | Firmly nonexpansive mapping | Normal cone operator | Fixed point | MATHEMATICS, APPLIED | affine subspace | normal cone operator | FEASIBILITY | projection operator | Attouch-Thera duality | SUM | maximally monotone operator | firmly nonexpansive mapping | fixed point | linear convergence | CONVERGENCE | normal problem | ALTERNATING PROJECTIONS | generalized solution | MONOTONE-OPERATORS

Journal Article

Mathematical programming, ISSN 1436-4646, 2016, Volume 164, Issue 1-2, pp. 263 - 284

The Douglas-Rachford algorithm is a very popular splitting technique for finding a zero of the sum of two maximally monotone operators...

Maximally monotone operator | Weak convergence | Sum problem | Douglas–Rachford algorithm | Inconsistent case | Paramonotone operator | Nonexpansive mapping | Attouch–Théra duality | FEASIBILITY PROBLEMS | MATHEMATICS, APPLIED | MAXIMAL MONOTONE-OPERATORS | Attouch-Thera duality | SUM | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Douglas-Rachford algorithm | CONSTRUCTION | CONVERGENCE | OPTIMIZATION | SUBSPACES | LINEAR-OPERATORS | HILBERT-SPACE | PROJECTIVE SPLITTING METHODS | Algorithms | Operators | Splitting | Approximation | Mathematical analysis | Clusters | Feasibility | Behavior | Convergence

Maximally monotone operator | Weak convergence | Sum problem | Douglas–Rachford algorithm | Inconsistent case | Paramonotone operator | Nonexpansive mapping | Attouch–Théra duality | FEASIBILITY PROBLEMS | MATHEMATICS, APPLIED | MAXIMAL MONOTONE-OPERATORS | Attouch-Thera duality | SUM | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Douglas-Rachford algorithm | CONSTRUCTION | CONVERGENCE | OPTIMIZATION | SUBSPACES | LINEAR-OPERATORS | HILBERT-SPACE | PROJECTIVE SPLITTING METHODS | Algorithms | Operators | Splitting | Approximation | Mathematical analysis | Clusters | Feasibility | Behavior | Convergence

Journal Article

Mathematics of operations research, ISSN 1526-5471, 2016, Volume 41, Issue 3, pp. 884 - 897

The problem of finding a minimizer of the sum of two convex functions—or, more generally, that of finding a zero of the sum of two maximally monotone operators...

firmly nonexpansive mapping | displacement mapping | near equality | subdifferential operator | convex function | nearly convex set | range | normal problem | Douglas–Rachford splitting operator | Brezis–Haraux theorem | maximally monotone operator | Attouch–Théra duality | Brezis-Haraux theorem | Maximally monotone operator | Near equality | Normal problem | Douglas-Rachford splitting operator | Nearly convex set | Firmly nonexpansive mapping | Subdifferential operator | Attouch-thera duality | Displacement mapping | Convex function | Range | MATHEMATICS, APPLIED | Attouch-Thera duality | SUM | PARAMONOTONICITY | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | DUALITY | MONOTONE-OPERATORS | Transformations (Mathematics) | Analysis | Convex functions

firmly nonexpansive mapping | displacement mapping | near equality | subdifferential operator | convex function | nearly convex set | range | normal problem | Douglas–Rachford splitting operator | Brezis–Haraux theorem | maximally monotone operator | Attouch–Théra duality | Brezis-Haraux theorem | Maximally monotone operator | Near equality | Normal problem | Douglas-Rachford splitting operator | Nearly convex set | Firmly nonexpansive mapping | Subdifferential operator | Attouch-thera duality | Displacement mapping | Convex function | Range | MATHEMATICS, APPLIED | Attouch-Thera duality | SUM | PARAMONOTONICITY | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | DUALITY | MONOTONE-OPERATORS | Transformations (Mathematics) | Analysis | Convex functions

Journal Article

Vietnam Journal of Mathematics, ISSN 2305-221X, 12/2014, Volume 42, Issue 4, pp. 451 - 465

In this paper we consider the inclusion problem involving a maximally monotone operator, a monotone and Lipschitz continuous operator, linear compositions of parallel-sum type monotone operators...

65K05 | Fitzpatrick function | Infimal-convolution | Subdifferential | Convex minimization problem | Mathematics | Lipschitz continuous operator | Parallel-sum | Maximally monotone operator | Resolvent | 90C25 | Mathematics, general | Forward–backward–forward algorithm | Fenchel conjugate | 47H05

65K05 | Fitzpatrick function | Infimal-convolution | Subdifferential | Convex minimization problem | Mathematics | Lipschitz continuous operator | Parallel-sum | Maximally monotone operator | Resolvent | 90C25 | Mathematics, general | Forward–backward–forward algorithm | Fenchel conjugate | 47H05

Journal Article

Mathematical Programming, ISSN 0025-5610, 2015, Volume 150, Issue 2, pp. 251 - 279

...) for solving monotone inclusion problems. Under strong monotonicity assumptions for some of the operators involved we obtain for the sequences of iterates that approach the solution orders of convergence of and , for...

Maximally monotone operator | Resolvent | Subdifferential | Operator splitting | Convex optimization algorithm | Duality | Strongly monotone operator | Strongly convex function | MATHEMATICS, APPLIED | COMPOSITE | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | MAPPINGS | OPERATORS | Algorithms | Image processing | Mathematical optimization | Analysis | Studies | Optimization algorithms | Mathematical analysis | Operators | Splitting | Texts | Pattern recognition | Inclusions | Optimization | Convergence

Maximally monotone operator | Resolvent | Subdifferential | Operator splitting | Convex optimization algorithm | Duality | Strongly monotone operator | Strongly convex function | MATHEMATICS, APPLIED | COMPOSITE | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | MAPPINGS | OPERATORS | Algorithms | Image processing | Mathematical optimization | Analysis | Studies | Optimization algorithms | Mathematical analysis | Operators | Splitting | Texts | Pattern recognition | Inclusions | Optimization | Convergence

Journal Article

Mathematical Programming, ISSN 0025-5610, 3/2018, Volume 168, Issue 1, pp. 55 - 61

The problem of finding a zero of the sum of two maximally monotone operators is of central importance in optimization...

Theoretical, Mathematical and Computational Physics | Primary 47H09 | Proximal mapping | Mathematics | Nowhere dense set | Maximally monotone operator | Mathematical Methods in Physics | Resolvent | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Firmly nonexpansive mapping | Douglas–Rachford algorithm | Combinatorics | Secondary 47H05 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Douglas-Rachford algorithm | POINT ALGORITHM | Algorithms | Operators | Mapping

Theoretical, Mathematical and Computational Physics | Primary 47H09 | Proximal mapping | Mathematics | Nowhere dense set | Maximally monotone operator | Mathematical Methods in Physics | Resolvent | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Firmly nonexpansive mapping | Douglas–Rachford algorithm | Combinatorics | Secondary 47H05 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Douglas-Rachford algorithm | POINT ALGORITHM | Algorithms | Operators | Mapping

Journal Article

Proceedings of the American Mathematical Society, ISSN 0002-9939, 05/2020, Volume 148, Issue 5, pp. 2035 - 2044

In his recent Proceedings of the AMS paper, ``Gossez's skew linear map and its pathological maximally monotone multifunctions'', Stephen Simons proved...

MATHEMATICS | MATHEMATICS, APPLIED | Gossez operator | Duality map | skew operator | range | Fitzpatrick-Phelps operator | maximally monotone operator

MATHEMATICS | MATHEMATICS, APPLIED | Gossez operator | Duality map | skew operator | range | Fitzpatrick-Phelps operator | maximally monotone operator

Journal Article