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Calculus rules for global approximate minima and applications to approximate subdifferential calculus
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-642-02431-3_10openalex-snapshot
Subdifferential Calculus
inferredcites →https://doi.org/10.1007/978-3-662-02796-7openalex-snapshot
Convex analysis and minimization algorithms
inferredcites →https://doi.org/10.1007/bf00250669openalex-snapshot
A duality principle for non-convex optimisation and the calculus of variations
inferredcites →https://doi.org/10.1007/bf01580767openalex-snapshot
Concave duality: Application to problems dealing with difference of functions
inferredcites →https://doi.org/10.1016/0041-5553(65)90148-5openalex-snapshot
Extremum problems in the presence of restrictions
inferredcites →https://doi.org/10.1017/s0004972700010844openalex-snapshot
A Fenchel-Rockafellar type duality theorem for maximization
inferredcites →https://doi.org/10.1017/s0004972700012569openalex-snapshot
A formula on the subdifferential of the deconvolution of convex functions
inferredcites →https://doi.org/10.1017/s0004972700036984openalex-snapshot
A formula on the approximate subdifferential of the difference of convex functions
inferredcites →https://doi.org/10.1137/0804038openalex-snapshot
Sensitivity Analysis of Optimal Value Functions of Convex Parametric Programs with Possibly Empty Solution Sets
inferredcites →https://doi.org/10.1137/1.9781611970524openalex-snapshot
Conjugate Duality and Optimization
inferredcites →https://doi.org/10.1137/1.9781611970524.ch1openalex-snapshot
1. Conjugate Duality and Optimization
inferredcites →https://doi.org/10.1215/s0012-7094-66-03312-6openalex-snapshot
Extension of Fenchel’ duality theorem for convex functions
inferredcites →https://doi.org/10.4153/cmb-1986-076-7openalex-snapshot
A General Formula on the Conjugate of the Difference of Functions
inferredcites →https://doi.org/10.5802/afst.721openalex-snapshot
Équations inf-convolutives et conjugaison de Moreau-Fenchel
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-36568-4_4openalex-snapshot
Characterizations of Robust and Stable Duality for Linearly Perturbed Uncertain Optimization Problems
inferred← citeshttps://doi.org/10.1007/bf00138691openalex-snapshot
Characterizing global optimality for DC optimization problems under convex inequality constraints
inferred← citeshttps://doi.org/10.1007/s10107-020-01494-1openalex-snapshot
Duality for constrained robust sum optimization problems
inferred← citeshttps://doi.org/10.1007/s10957-018-1431-1openalex-snapshot
Differential Stability of Convex Optimization Problems with Possibly Empty Solution Sets
inferred← citeshttps://doi.org/10.1007/s10957-024-02400-xopenalex-snapshot
Differential Stability Properties of Convex Optimization and Optimal Control Problems
inferred← citeshttps://doi.org/10.1007/s11228-019-00515-2openalex-snapshot
Duality for the Robust Sum of Functions
inferred← citeshttps://doi.org/10.1007/s40314-025-03151-9openalex-snapshot
Epsilon-subdifferentiability for interval-valued functions and its application in interval optimization problems
inferred← citeshttps://doi.org/10.1016/0362-546x(94)00221-3openalex-snapshot
Subdifferential calculus without qualification conditions, using approximate subdifferentials: A survey
inferred← citeshttps://doi.org/10.1016/j.cam.2026.118077openalex-snapshot
Projected subgradient method for nonsmooth interval optimization problems with application
inferred← citeshttps://doi.org/10.1080/02331934.2019.1687697openalex-snapshot
Differential stability of convex optimization problems under weaker conditions
inferred← citeshttps://doi.org/10.1080/02331934.2020.1836637openalex-snapshot
Differential stability of convex discrete optimal control problems with possibly empty solution sets
inferred← citeshttps://doi.org/10.4213/im192openalex-snapshot
О субдифференциале и производных по направлениям максимума семейства выпуклых функций
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