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A class of almost-differentiable functions and a minimization method for functions of this class
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inferredcites →https://doi.org/10.1007/bf01068282openalex-snapshot
Convergence conditions of a minimization method of almost-differentiable functions
inferredcites →https://doi.org/10.1007/bf01071708openalex-snapshot
The penalty method in convex programming
inferredcites →https://doi.org/10.1070/rm1970v025n01abeh001255openalex-snapshot
THE GENERAL THEORY OF RELAXATION PROCESSES FOR CONVEX FUNCTIONALS
inferredcites →https://doi.org/10.1201/9781003064848openalex-snapshot
Necessary Conditions for an Extremum
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Shor’s r-Algorithms: Theory and Practice
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Optimization of Generalized $$C_p$$ Criterion for Selecting Ridge Parameters in Generalized Ridge Regression
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On a space extension algorithm for nondifferentiable optimization
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Descent algorithm for a class of convex nondifferentiable functions
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Convergence conditions of a minimization method of almost-differentiable functions
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On necessary conditions for an extremum for nondifferentiable functions
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A method for the minimization of almost-differentiable functions
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Generalized-differentiable functions
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Superlinearly convergent approximate Newton methods for LC1 optimization problems
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On optimality conditions in nondifferentiable programming
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On the characterization and the computation of the characteristic function of a game without side payments
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An approach to the solution of nonlinear unconstrained optimization problems
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On the development of software support for solving problems of optimal design of power boilers
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Theory and Software Implementations of Shor’s r-Algorithms*
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A note on the generalized differentiability of mappings
inferred← citeshttps://doi.org/10.1016/b978-0-12-468660-1.50021-9openalex-snapshot
MINIMISATION DE FONCTIONS LOCALEMENT LIPSCHITZIENNES: APPLICATIONS A LA PROGRAMMATION MI-CONVEXE, MI-DIFFERENTIABLE
inferred← citeshttps://doi.org/10.1016/b978-0-12-468662-5.50016-1openalex-snapshot
CONVERGENCE RESULTS IN A CLASS OF VARIABLE METRIC SUBGRADIENT METHODS11This research was supported in part by the D.G.E.S. (Quebec), the N.S.E.R.C. of Canada under grant A 4152, and the S.S.H.R.C. of Canada.
inferred← citeshttps://doi.org/10.1016/j.na.2011.06.039openalex-snapshot
Generalized Newton’s method based on graphical derivatives
inferred← citeshttps://doi.org/10.1080/01630568008816042openalex-snapshot
Mean value theorems in nonsmooth analysis
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Solving Systems of Random Quadratic Equations via Truncated Amplitude Flow
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An Algorithm for Constrained Optimization with Semismooth Functions
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New concepts in nondifferentiable programming
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