REVIEW 1 cited by
Second-Order Subdifferential Optimality Conditions in Nonsmooth Optimization
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
The paper is devoted to deriving novel second-order necessary and sufficient optimality conditions for local minimizers in rather general classes of nonsmooth unconstrained and constrained optimization problems in finite-dimensional spaces. The established conditions are expressed in terms of second-order subdifferentials of lower semicontinuous functions and mainly concern prox-regular objectives that cover a large territory in nonsmooth optimization and its applications. Our tools are based on the machinery of variational analysis and second-order generalized differentiation. The obtained general results are applied to problems of nonlinear programming, where the derived second-order optimality conditions are new even for problems with twice continuously differential data, being expressed there in terms of the classical Hessian matrices.
Forward citations
Cited by 1 Pith paper
-
On the hardness of deterministic second-order optimization of functions with Lipschitz gradients
No deterministic zero-respecting second-order algorithm can compute Goldstein approximate second-order stationary points of C^{1,1} functions within finitely many oracle calls; general deterministic algorithms need at...
Discussion (0). Continue with ORCID to comment.