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On the superlinear convergence of the variable metric proximal point algorithm using Broyden and BFGS matrix secant updating
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Outgoing claims: the papers this work cites, builds on, or argues with.
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A family of variable metric proximal methods
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A descent algorithm for nonsmooth convex optimization
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A quasi-second-order proximal bundle algorithm
inferredcites →https://doi.org/10.1007/bf02614390openalex-snapshot
Variable metric bundle methods: From conceptual to implementable forms
inferredcites →https://doi.org/10.1007/bf02614391openalex-snapshot
A preconditioning proximal newton method for nondifferentiable convex optimization
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An approach to variable metric bundle methods
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Proximal quasi-Newton methods for nondifferentiable convex optimization
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A Characterization of Superlinear Convergence and Its Application to Quasi-Newton Methods
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Numerical Methods for Unconstrained Optimization and Nonlinear Equations
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A Variable Metric Proximal Point Algorithm for Monotone Operators
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A Globally and Superlinearly Convergent Algorithm for Nonsmooth Convex Minimization
inferredcites →https://doi.org/10.1137/s1052623496303329openalex-snapshot
Quasi-Newton Bundle-Type Methods for Nondifferentiable Convex Optimization
inferredcites →https://doi.org/10.24033/bsmf.1625openalex-snapshot
Proximité et dualité dans un espace hilbertien
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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On the Local Super-Linear Convergence of a Matrix Secant Implementation of the Variable Metric Proximal Point Algorithm for Monotone Operators
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Customized proximal point algorithms for linearly constrained convex minimization and saddle-point problems: a unified approach
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The Developments of Proximal Point Algorithms
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Tseng’s Algorithm with Extrapolation from the past Endowed with Variable Metrics and Error Terms
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