Computing B-Stationary Points of Nonsmooth DC Programs
From MaRDI portal
Publication:2976143
DOI10.1287/moor.2016.0795zbMath1359.90106arXiv1511.01796OpenAlexW2225235077MaRDI QIDQ2976143
Alberth Alvarado, Jong-Shi Pang, Meisam Razaviyayn
Publication date: 13 April 2017
Published in: Mathematics of Operations Research (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1511.01796
randomizationstationary solutionsDC algorithmDC constraintsBouligand derivativesnonsmooth DC programming
Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Communication networks in operations research (90B18)
Related Items
Alternating DC algorithm for partial DC programming problems, Feasible methods for nonconvex nonsmooth problems with applications in green communications, The ABC of DC programming, Addendum to the paper ‘Nonsmooth DC-constrained optimization: constraint qualification and minimizing methodologies’, The DTC (difference of tangentially convex functions) programming: optimality conditions, Nonconvex and nonsmooth approaches for affine chance-constrained stochastic programs, Composite Difference-Max Programs for Modern Statistical Estimation Problems, A unifying framework of high-dimensional sparse estimation with difference-of-convex (DC) regularizations, Some brief observations in minimizing the sum of locally Lipschitzian functions, Difference-of-Convex Algorithms for a Class of Sparse Group $\ell_0$ Regularized Optimization Problems, Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algorithms, Difference-of-Convex Learning: Directional Stationarity, Optimality, and Sparsity, Solving constrained nonsmooth group sparse optimization via group Capped-\(\ell_1\) relaxation and group smoothing proximal gradient algorithm, Zero-norm regularized problems: equivalent surrogates, proximal MM method and statistical error bound, Neural network for a class of sparse optimization with \(L_0\)-regularization, On Robustness of Individualized Decision Rules, Study on \(L_1\) over \(L_2\) Minimization for nonnegative signal recovery, Short paper -- A note on the Frank-Wolfe algorithm for a class of nonconvex and nonsmooth optimization problems, Structural properties of affine sparsity constraints, Computation of the maximum likelihood estimator in low-rank factor analysis, Enhanced proximal DC algorithms with extrapolation for a class of structured nonsmooth DC minimization, Convergence rate analysis of an extrapolated proximal difference-of-convex algorithm, A refined inertial DC algorithm for DC programming, A DCA-Newton method for quartic minimization over the sphere, A global two-stage algorithm for non-convex penalized high-dimensional linear regression problems, Sequential difference-of-convex programming, Hybrid Algorithms for Finding a D-Stationary Point of a Class of Structured Nonsmooth DC Minimization, MultiComposite Nonconvex Optimization for Training Deep Neural Networks, Minimizing sequences in a constrained DC optimization problem, Open issues and recent advances in DC programming and DCA, Retraction-based first-order feasible methods for difference-of-convex programs with smooth inequality and simple geometric constraints, Linear-step solvability of some folded concave and singly-parametric sparse optimization problems, Difference of convex algorithms for bilevel programs with applications in hyperparameter selection, A smoothing proximal gradient algorithm with extrapolation for the relaxation of \({\ell_0}\) regularization problem, A matrix nonconvex relaxation approach to unconstrained binary polynomial programs, Lifted stationary points of sparse optimization with complementarity constraints, Error bound and isocost imply linear convergence of DCA-based algorithms to D-stationarity, Unnamed Item, Non-smooth DC-constrained optimization: constraint qualification and minimizing methodologies, Unnamed Item, On the superiority of PGMs to PDCAs in nonsmooth nonconvex sparse regression, An augmented subgradient method for minimizing nonsmooth DC functions, Several Classes of Stationary Points for Rank Regularized Minimization Problems, On the pervasiveness of difference-convexity in optimization and statistics, Decomposition Methods for Computing Directional Stationary Solutions of a Class of Nonsmooth Nonconvex Optimization Problems, DC programming and DCA: thirty years of developments, A study of the difference-of-convex approach for solving linear programs with complementarity constraints, Robust multicategory support vector machines using difference convex algorithm, Iteratively Reweighted Group Lasso Based on Log-Composite Regularization, Consistency bounds and support recovery of d-stationary solutions of sparse sample average approximations, Proximal bundle methods for nonsmooth DC programming, Nonconvex robust programming via value-function optimization, A bundle method for nonsmooth DC programming with application to chance-constrained problems, Optimizing power generation in the presence of micro-grids, An inertial algorithm for DC programming, On the Convergence to Stationary Points of Deterministic and Randomized Feasible Descent Directions Methods, Computation of second-order directional stationary points for group sparse optimization, Piecewise affine parameterized value-function based bilevel non-cooperative games, Two-Stage Stochastic Programming with Linearly Bi-parameterized Quadratic Recourse, Nonsmooth and nonconvex optimization via approximate difference-of-convex decompositions, Estimation of Individualized Decision Rules Based on an Optimized Covariate-Dependent Equivalent of Random Outcomes, Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming, Unnamed Item, A general double-proximal gradient algorithm for d.c. programming, Dual Randomized Coordinate Descent Method for Solving a Class of Nonconvex Problems, Convergence Rate Analysis of a Sequential Convex Programming Method with Line Search for a Class of Constrained Difference-of-Convex Optimization Problems, Asymptotic Properties of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization, Penalty and Augmented Lagrangian Methods for Constrained DC Programming, Extrapolated Proximal Subgradient Algorithms for Nonconvex and Nonsmooth Fractional Programs, Stochastic Difference-of-Convex-Functions Algorithms for Nonconvex Programming, Solving Nonsmooth and Nonconvex Compound Stochastic Programs with Applications to Risk Measure Minimization
Uses Software
Cites Work
- Unnamed Item
- On conic QPCCs, conic QCQPs and completely positive programs
- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- On solving linear complementarity problems by DC programming and DCA
- Exact penalty and error bounds in DC programming
- On almost smooth functions and piecewise smooth functions
- On the difference of two maximal monotone operators: Regularization and algorithmic approaches
- OPECgen, a MATLAB generator for mathematical programs with quadratic objectives and affine variational inequality constraints
- Complementarity constraint qualifications and simplified \(B\)-stationary conditions for mathematical programs with equilibrium constraints
- Directionally nondifferentiable metric projection
- The DC (Difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
- Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
- On convex quadratic programs with linear complementarity constraints
- Mathematical Programs with Complementarity Constraints: Stationarity, Optimality, and Sensitivity
- A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization
- A Proof of Convergence of the Concave-Convex Procedure Using Zangwill's Theory
- DC Programming and DCA for General DC Programs
- Nonconvex Games with Side Constraints
- Convergence of New Inertial Proximal Methods for DC Programming
- Nonconvex Structures in Nonlinear Programming
- Global minimization of a difference of two convex functions
- Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems
- Optimal Joint Base Station Assignment and Beamforming for Heterogeneous Networks
- A New Decomposition Method for Multiuser DC-Programming and Its Applications
- Parallel Selective Algorithms for Nonconvex Big Data Optimization
- Finite-Dimensional Variational Inequalities and Complementarity Problems
- Partially B-Regular Optimization and Equilibrium Problems
- Two Convex Counterexamples: A Discontinuous Envelope Function and a Nondifferentiable Nearest-Point Mapping