Computing B-Stationary Points of Nonsmooth DC Programs
Not on the map. Why?
Abstract (arXiv)
Motivated by a class of applied problems arising from physical layer based security in a digital communication system, in particular, by a secrecy sum-rate maximization problem, this paper studies a nonsmooth, difference-of-convex (dc) minimization problem. The contributions of this paper are: (i) clarify several kinds of stationary solutions and their relations; (ii) develop and establish the convergence of a novel algorithm for computing a d-stationary solution of a problem with a convex feasible set that is arguably the sharpest kind among the various stationary solutions; (iii) extend the algorithm in several directions including: a randomized choice of the subproblems that could help the practical convergence of the algorithm, a distributed penalty approach for problems whose objective functions are sums of dc functions, and problems with a specially structured (nonconvex) dc constraint. For the latter class of problems, a pointwise Slater constraint qualification is introduced that facilitates the verification and computation of a B(ouligand)-stationary point.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Nov 2015.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 2; 2022: 2; 2023: 1; 2024: 2; 2025: 2; 2026: 3.
12 papers.
- 2022Large-scale Optimization of Partial AUC in a Range of False Positive Ratescited by 15
- 2024Non-geodesically-convex optimization in the Wasserstein spacecited by 5
- 2021Coordinate Descent Methods for DC Minimization: Optimality Conditions and Global Convergencecited by 2
- 2022Coordinate Descent Methods for Fractional Minimizationcited by 2
- 2025Enforcing Fair Predicted Scores on Intervals of Percentiles by Difference-of-Convex Constraintscited by 2
- 2024Learning Robust Treatment Rules for Censored Datacited by 1
- 2025A stochastic smoothing framework for nonconvex-nonconcave minEmax problems with applications to Wasserstein distributionally robust optimizationcited by 1
- 2021A Refined Inertial DC Algorithm for DC Programmingcited by 0
- 2023An inexact LPA for DC composite optimization and application to matrix completions with outlierscited by 0
- 2026RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programscited by 0
- 2026MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-Regularized Optimizationcited by 0
- 2026Online Optimization of Difference-of-Convex Compositions with Smooth Mappingscited by 0
- 2026Online Optimization of Difference-of-Convex Compositions with Smooth Mappings21 Jul 2026
- 2026MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-Regularized Optimization28 May 2026
- 2026RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs22 May 2026
- 2025Enforcing Fair Predicted Scores on Intervals of Percentiles by Difference-of-Convex Constraints18 May 2025
- 2025A stochastic smoothing framework for nonconvex-nonconcave minEmax problems with applications to Wasserstein distributionally robust optimization24 Feb 2025
- 2024Learning Robust Treatment Rules for Censored Data17 Aug 2024
- 2024Non-geodesically-convex optimization in the Wasserstein space1 Jun 2024
- 2023An inexact LPA for DC composite optimization and application to matrix completions with outliers29 Mar 2023
- 2022Large-scale Optimization of Partial AUC in a Range of False Positive Rates3 Mar 2022
- 2022Coordinate Descent Methods for Fractional Minimization30 Jan 2022
- 2021Coordinate Descent Methods for DC Minimization: Optimality Conditions and Global Convergence9 Sep 2021
- 2021A Refined Inertial DC Algorithm for DC Programming30 Apr 2021