Mathematical Programming, ISSN 0025-5610, 9/2009, Volume 120, Issue 2, pp. 479 - 495

In this paper, we model any nonconvex quadratic program having a mix of binary and continuous variables as a linear program over the dual of the cone of...

90C20 | Mathematical Methods in Physics | Mathematics of Computing | Calculus of Variations and Optimal Control; Optimization | 90C25 | Mathematical and Computational Physics | Numerical Analysis | Mathematics | 90C26 | Combinatorics | Mathematics Subject Classification : 90C25 | STABILITY NUMBER | GRAPH | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | SEMIDEFINITE RELAXATIONS | OPTIMIZATION PROBLEMS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Management science | Studies | Linear programming | Mathematical programming

90C20 | Mathematical Methods in Physics | Mathematics of Computing | Calculus of Variations and Optimal Control; Optimization | 90C25 | Mathematical and Computational Physics | Numerical Analysis | Mathematics | 90C26 | Combinatorics | Mathematics Subject Classification : 90C25 | STABILITY NUMBER | GRAPH | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | SEMIDEFINITE RELAXATIONS | OPTIMIZATION PROBLEMS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Management science | Studies | Linear programming | Mathematical programming

Journal Article

Mathematical Programming, ISSN 0025-5610, 6/2015, Volume 151, Issue 1, pp. 3 - 34

Coordinate descent algorithms solve optimization problems by successively performing approximate minimization along coordinate directions or coordinate...

Parallel numerical computing | 49M20 | Mathematical Methods in Physics | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Theoretical, Mathematical and Computational Physics | Randomized algorithms | Mathematics | Combinatorics | Coordinate descent | REGRESSION | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | SHRINKAGE | CONVERGENCE | OPTIMIZATION | Analysis | Algorithms | Machine learning | Studies | Optimization algorithms

Parallel numerical computing | 49M20 | Mathematical Methods in Physics | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Theoretical, Mathematical and Computational Physics | Randomized algorithms | Mathematics | Combinatorics | Coordinate descent | REGRESSION | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | SHRINKAGE | CONVERGENCE | OPTIMIZATION | Analysis | Algorithms | Machine learning | Studies | Optimization algorithms

Journal Article

Mathematical Programming, ISSN 0025-5610, 8/2013, Volume 140, Issue 1, pp. 125 - 161

In this paper we analyze several new methods for solving optimization problems with the objective function formed as a sum of two terms: one is smooth and...

68Q25 | Theoretical, Mathematical and Computational Physics | Mathematics | Complexity theory | Black-box model | Local optimization | l_1$$ -Regularization | Mathematical Methods in Physics | Optimal methods | Structural optimization | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | 90C47 | Numerical Analysis | Convex Optimization | Nonsmooth optimization | Combinatorics | 1-Regularization | MATHEMATICS, APPLIED | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | DECONVOLUTION | MINIMIZATION | l-Regularization | Studies | Mathematical models | Optimization | Mathematical programming | Composite functions | Computation | Mathematical analysis | Iterative methods | Descent | Convergence

68Q25 | Theoretical, Mathematical and Computational Physics | Mathematics | Complexity theory | Black-box model | Local optimization | l_1$$ -Regularization | Mathematical Methods in Physics | Optimal methods | Structural optimization | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | 90C47 | Numerical Analysis | Convex Optimization | Nonsmooth optimization | Combinatorics | 1-Regularization | MATHEMATICS, APPLIED | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | DECONVOLUTION | MINIMIZATION | l-Regularization | Studies | Mathematical models | Optimization | Mathematical programming | Composite functions | Computation | Mathematical analysis | Iterative methods | Descent | Convergence

Journal Article

Mathematical Programming, ISSN 0025-5610, 6/2011, Volume 128, Issue 1, pp. 321 - 353

The linearly constrained matrix rank minimization problem is widely applicable in many fields such as control, signal processing and system identification. The...

65K05 | Theoretical, Mathematical and Computational Physics | 90C06 | Mathematics | Matrix completion problem | Fixed point iterative method | Mathematical Methods in Physics | Nuclear norm minimization | Mathematics of Computing | Calculus of Variations and Optimal Control; Optimization | 90C25 | Numerical Analysis | Matrix rank minimization | Combinatorics | 93C41 | 68Q32 | Bregman distances | Singular value decomposition | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | PROGRAMS | NOISE | ALGORITHMS | Algorithms | DNA microarrays | Management science | Analysis | Methods | Studies | Matrix | Iterative methods | Mathematical programming | Constraints | Images | Norms | Programming | Minimization | Matrices | Optimization

65K05 | Theoretical, Mathematical and Computational Physics | 90C06 | Mathematics | Matrix completion problem | Fixed point iterative method | Mathematical Methods in Physics | Nuclear norm minimization | Mathematics of Computing | Calculus of Variations and Optimal Control; Optimization | 90C25 | Numerical Analysis | Matrix rank minimization | Combinatorics | 93C41 | 68Q32 | Bregman distances | Singular value decomposition | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | PROGRAMS | NOISE | ALGORITHMS | Algorithms | DNA microarrays | Management science | Analysis | Methods | Studies | Matrix | Iterative methods | Mathematical programming | Constraints | Images | Norms | Programming | Minimization | Matrices | Optimization

Journal Article

Mathematical Programming, ISSN 0025-5610, 1/2016, Volume 155, Issue 1, pp. 57 - 79

The alternating direction method of multipliers (ADMM) is now widely used in many fields, and its convergence was proved when two blocks of variables are...

Alternating direction method of multipliers | Theoretical, Mathematical and Computational Physics | Mathematics | Convex programming | Convergence analysis | Mathematical Methods in Physics | Splitting methods | 90C30 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Combinatorics | 65K13 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Yuan (China) | Management techniques | Management science | Management | Analysis | Studies | Mathematical analysis | Convex analysis | Convergence | Mathematical programming | Functions (mathematics) | Multipliers | Divergence | Minimization | Optimization

Alternating direction method of multipliers | Theoretical, Mathematical and Computational Physics | Mathematics | Convex programming | Convergence analysis | Mathematical Methods in Physics | Splitting methods | 90C30 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Combinatorics | 65K13 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | Yuan (China) | Management techniques | Management science | Management | Analysis | Studies | Mathematical analysis | Convex analysis | Convergence | Mathematical programming | Functions (mathematics) | Multipliers | Divergence | Minimization | Optimization

Journal Article

Journal of Optimization Theory and Applications, ISSN 0022-3239, 9/2015, Volume 166, Issue 3, pp. 968 - 982

We discuss here the convergence of the iterates of the â€śFast Iterative Shrinkage/Thresholding Algorithm,â€ť which is an algorithm proposed by Beck and Teboulle...

Forward backward splitting | Inertial algorithms | Mathematics | Theory of Computation | 65Y20 | Optimization | Convergence | 65B99 | Calculus of Variations and Optimal Control; Optimization | 90C25 | Operations Research/Decision Theory | Applications of Mathematics | Engineering, general | First-order schemes

Forward backward splitting | Inertial algorithms | Mathematics | Theory of Computation | 65Y20 | Optimization | Convergence | 65B99 | Calculus of Variations and Optimal Control; Optimization | 90C25 | Operations Research/Decision Theory | Applications of Mathematics | Engineering, general | First-order schemes

Journal Article

Foundations of Computational Mathematics, ISSN 1615-3375, 12/2012, Volume 12, Issue 6, pp. 805 - 849

In applications throughout science and engineering one is often faced with the challenge of solving an ill-posed inverse problem, where the number of available...

60D05 | Semidefinite programming | Economics general | 52A41 | Linear and Multilinear Algebras, Matrix Theory | Mathematics | Real algebraic geometry | 41A45 | Convex optimization | 90C25 | Numerical Analysis | 90C22 | Atomic norms | Math Applications in Computer Science | Applications of Mathematics | Computer Science, general | Gaussian width | Symmetry | MATHEMATICS, APPLIED | TENSOR DECOMPOSITIONS | APPROXIMATION | ALGORITHM | INEQUALITY | EQUATIONS | RANK | MATHEMATICS | RECOVERY | MINIMIZATION | NORM | BODIES | COMPUTER SCIENCE, THEORY & METHODS | Geometry | Computational mathematics | Algebra | Optimization | Inverse problems | Mathematical analysis | Norms | Programming | Mathematical models | Matrices | Atomic structure | Matrix methods

60D05 | Semidefinite programming | Economics general | 52A41 | Linear and Multilinear Algebras, Matrix Theory | Mathematics | Real algebraic geometry | 41A45 | Convex optimization | 90C25 | Numerical Analysis | 90C22 | Atomic norms | Math Applications in Computer Science | Applications of Mathematics | Computer Science, general | Gaussian width | Symmetry | MATHEMATICS, APPLIED | TENSOR DECOMPOSITIONS | APPROXIMATION | ALGORITHM | INEQUALITY | EQUATIONS | RANK | MATHEMATICS | RECOVERY | MINIMIZATION | NORM | BODIES | COMPUTER SCIENCE, THEORY & METHODS | Geometry | Computational mathematics | Algebra | Optimization | Inverse problems | Mathematical analysis | Norms | Programming | Mathematical models | Matrices | Atomic structure | Matrix methods

Journal Article

Mathematical Programming, ISSN 0025-5610, 9/2011, Volume 129, Issue 1, pp. 69 - 89

We consider the problems of finding a maximum clique in a graph and finding a maximum-edge biclique in a bipartite graph. Both problems are NP-hard. We write...

68Q25 | Mathematical Methods in Physics | 65K05 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Theoretical, Mathematical and Computational Physics | Mathematics | Combinatorics | Mathematics Subject Classification : 90C25 | GRAPH | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | LARGE HIDDEN CLIQUE | MATRICES | Analysis | Algorithms | Studies | Mathematical programming | Mathematical analysis | Exact solutions | Norms | Graphs | Minimization | Bypasses | Optimization

68Q25 | Mathematical Methods in Physics | 65K05 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Theoretical, Mathematical and Computational Physics | Mathematics | Combinatorics | Mathematics Subject Classification : 90C25 | GRAPH | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | LARGE HIDDEN CLIQUE | MATRICES | Analysis | Algorithms | Studies | Mathematical programming | Mathematical analysis | Exact solutions | Norms | Graphs | Minimization | Bypasses | Optimization

Journal Article

Numerische Mathematik, ISSN 0029-599X, 7/2015, Volume 130, Issue 3, pp. 567 - 577

This note proposes a novel approach to derive a worst-case $$O(1/k)$$ O ( 1 / k ) convergence rate measured by the iteration complexity in a non-ergodic sense...

Mathematical Methods in Physics | 90C30 | 90C25 | Numerical Analysis | Theoretical, Mathematical and Computational Physics | Appl.Mathematics/Computational Methods of Engineering | Numerical and Computational Physics | Mathematics, general | Mathematics | MATHEMATICS, APPLIED | Yuan (China) | Methods

Mathematical Methods in Physics | 90C30 | 90C25 | Numerical Analysis | Theoretical, Mathematical and Computational Physics | Appl.Mathematics/Computational Methods of Engineering | Numerical and Computational Physics | Mathematics, general | Mathematics | MATHEMATICS, APPLIED | Yuan (China) | Methods

Journal Article

Mathematical Programming, ISSN 0025-5610, 4/2014, Volume 144, Issue 1, pp. 1 - 38

In this paper we develop a randomized block-coordinate descent method for minimizing the sum of a smooth and a simple nonsmooth block-separable convex function...

65K05 | Theoretical, Mathematical and Computational Physics | Block coordinate descent | 90C06 | Mathematics | Sparse regression | 90C05 | Iteration complexity | Gradient descent | Mathematical Methods in Physics | Gaussâ€“Seidel method | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | Composite minimization | Convex optimization | Coordinate relaxation | 90C25 | Numerical Analysis | Huge-scale optimization | LASSO | Combinatorics | Gauss-Seidel method | REGRESSION | MATHEMATICS, APPLIED | ALGORITHM | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | CONVERGENCE | OPTIMIZATION | SELECTION | Methods | Algorithms | Studies | Regression analysis | Optimization | Mathematical programming | Least squares method | Mathematical analysis | Blocking | Texts | Mathematical models | Iterative methods | Descent | Complexity

65K05 | Theoretical, Mathematical and Computational Physics | Block coordinate descent | 90C06 | Mathematics | Sparse regression | 90C05 | Iteration complexity | Gradient descent | Mathematical Methods in Physics | Gaussâ€“Seidel method | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | Composite minimization | Convex optimization | Coordinate relaxation | 90C25 | Numerical Analysis | Huge-scale optimization | LASSO | Combinatorics | Gauss-Seidel method | REGRESSION | MATHEMATICS, APPLIED | ALGORITHM | COMPUTER SCIENCE, SOFTWARE ENGINEERING | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MINIMIZATION | CONVERGENCE | OPTIMIZATION | SELECTION | Methods | Algorithms | Studies | Regression analysis | Optimization | Mathematical programming | Least squares method | Mathematical analysis | Blocking | Texts | Mathematical models | Iterative methods | Descent | Complexity

Journal Article

Mathematical Programming, ISSN 0025-5610, 3/2017, Volume 162, Issue 1, pp. 83 - 112

We analyze the stochastic average gradient (SAG) method for optimizing the sum of a finite number of smooth convex functions. Like stochastic gradient (SG)...

68Q25 | 65K05 | Theoretical, Mathematical and Computational Physics | 90C06 | Mathematics | Stochastic gradient methods | 90C15 | First-order methods | Mathematical Methods in Physics | 90C30 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | Convex optimization | 90C25 | Numerical Analysis | Convergence Rates | Combinatorics | 62L20 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | APPROXIMATION | ALGORITHMS | Analysis | Algorithms | Studies | Convex analysis | Optimization | Mathematical analysis | Sag | Texts | Strategy | Mathematical models | Stochasticity | Sampling | Convergence

68Q25 | 65K05 | Theoretical, Mathematical and Computational Physics | 90C06 | Mathematics | Stochastic gradient methods | 90C15 | First-order methods | Mathematical Methods in Physics | 90C30 | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | Convex optimization | 90C25 | Numerical Analysis | Convergence Rates | Combinatorics | 62L20 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | APPROXIMATION | ALGORITHMS | Analysis | Algorithms | Studies | Convex analysis | Optimization | Mathematical analysis | Sag | Texts | Strategy | Mathematical models | Stochasticity | Sampling | Convergence

Journal Article

Journal of Optimization Theory and Applications, ISSN 0022-3239, 6/2016, Volume 169, Issue 3, pp. 1042 - 1068

We introduce a first-order method for solving very large convex cone programs. The method uses an operator splitting method, the alternating directions method...

90C06 | Mathematics | Theory of Computation | First-order methods | Optimization | Calculus of Variations and Optimal Control; Optimization | 90C25 | Cone programming | Operator splitting | 49M29 | 49M05 | Applications of Mathematics | Engineering, general | Operation Research/Decision Theory | PROJECTION | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | ALGORITHM | SETS | DECOMPOSITION | SYSTEMS | INVERSE | Electrical engineering | Computer science | Studies | Mathematical programming | Freeware | Operators | Splitting | Mathematical models | Subspaces | Intersections | Source code

90C06 | Mathematics | Theory of Computation | First-order methods | Optimization | Calculus of Variations and Optimal Control; Optimization | 90C25 | Cone programming | Operator splitting | 49M29 | 49M05 | Applications of Mathematics | Engineering, general | Operation Research/Decision Theory | PROJECTION | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | ALGORITHM | SETS | DECOMPOSITION | SYSTEMS | INVERSE | Electrical engineering | Computer science | Studies | Mathematical programming | Freeware | Operators | Splitting | Mathematical models | Subspaces | Intersections | Source code

Journal Article

Mathematical Programming Computation, ISSN 1867-2949, 6/2013, Volume 5, Issue 2, pp. 201 - 226

This paper develops Jellyfish, an algorithm for solving data-processing problems with matrix-valued decision variables regularized to have low rank. Particular...

Multicore | Parallel computing | Mathematics of Computing | 90C25 | Operations Research/Decision Theory | Incremental gradient methods | 90C06 | Mathematics | Theory of Computation | 90C15 | Optimization | Matrix completion

Multicore | Parallel computing | Mathematics of Computing | 90C25 | Operations Research/Decision Theory | Incremental gradient methods | 90C06 | Mathematics | Theory of Computation | 90C15 | Optimization | Matrix completion

Journal Article

Journal of Fourier Analysis and Applications, ISSN 1069-5869, 12/2013, Volume 19, Issue 6, pp. 1229 - 1254

This paper studies the recovery of a superposition of point sources from noisy bandlimited data. In the fewest possible words, we only have information about...

Line spectra estimation | Basis mismatch | Signal, Image and Speech Processing | Mathematics | Stable signal recovery | Abstract Harmonic Analysis | Mathematical Methods in Physics | Deconvolution | Fourier Analysis | 42A15 | Sparsity | 90C25 | 90C22 | Approximations and Expansions | Super-resolution factor | 94A12 | Partial Differential Equations | FREQUENCIES | MUSIC | MATHEMATICS, APPLIED | RECONSTRUCTION | RESOLUTION | SIGNALS | PARAMETERS | MICROSCOPY | STATISTICAL-ANALYSIS | SINUSOIDS | DIFFRACTION-LIMIT | Electrical engineering

Line spectra estimation | Basis mismatch | Signal, Image and Speech Processing | Mathematics | Stable signal recovery | Abstract Harmonic Analysis | Mathematical Methods in Physics | Deconvolution | Fourier Analysis | 42A15 | Sparsity | 90C25 | 90C22 | Approximations and Expansions | Super-resolution factor | 94A12 | Partial Differential Equations | FREQUENCIES | MUSIC | MATHEMATICS, APPLIED | RECONSTRUCTION | RESOLUTION | SIGNALS | PARAMETERS | MICROSCOPY | STATISTICAL-ANALYSIS | SINUSOIDS | DIFFRACTION-LIMIT | Electrical engineering

Journal Article

Mathematical Programming, ISSN 0025-5610, 2/2013, Volume 137, Issue 1, pp. 453 - 476

We show that unless P = NP, there exists no polynomial time (or even pseudo-polynomial time) algorithm that can decide whether a multivariate polynomial of...

90C25 Convex programming | Mathematical Methods in Physics | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C60 Abstract computational complexity for mathematical programming problems | Numerical Analysis | Theoretical, Mathematical and Computational Physics | 68Q25 Analysis of algorithms & problem complexity | Mathematics | Combinatorics | Mathematics Subject Classification : 90C25 Convex programming | CRITERIA | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | COMPLEXITY | SETS | REPRESENTATION | OPTIMIZATION | Computer science | Electrical engineering | Mechanical properties | Algorithms | Hardness | Analysis | Studies | Polynomials | Multivariate analysis | Mathematical programming | Convexity | Complexity

90C25 Convex programming | Mathematical Methods in Physics | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C60 Abstract computational complexity for mathematical programming problems | Numerical Analysis | Theoretical, Mathematical and Computational Physics | 68Q25 Analysis of algorithms & problem complexity | Mathematics | Combinatorics | Mathematics Subject Classification : 90C25 Convex programming | CRITERIA | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | COMPLEXITY | SETS | REPRESENTATION | OPTIMIZATION | Computer science | Electrical engineering | Mechanical properties | Algorithms | Hardness | Analysis | Studies | Polynomials | Multivariate analysis | Mathematical programming | Convexity | Complexity

Journal Article

Mathematical Programming, ISSN 0025-5610, 3/2016, Volume 156, Issue 1, pp. 59 - 99

In this paper, we generalize the well-known Nesterovâ€™s accelerated gradient (AG) method, originally designed for convex smooth optimization, to solve nonconvex...

68Q25 | Nonconvex optimization | Theoretical, Mathematical and Computational Physics | Mathematics | 90C15 | Stochastic programming | Complexity | Mathematical Methods in Physics | Accelerated gradient | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Combinatorics | 62L20 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | APPROXIMATION ALGORITHMS | COMPOSITE OPTIMIZATION | Methods | Convergence (Social sciences) | Studies | Computer programming | Stochastic models | Nonlinear programming | Policies | Approximation | Mathematical analysis | Programming | Stochasticity | Optimization | Convergence

68Q25 | Nonconvex optimization | Theoretical, Mathematical and Computational Physics | Mathematics | 90C15 | Stochastic programming | Complexity | Mathematical Methods in Physics | Accelerated gradient | Calculus of Variations and Optimal Control; Optimization | Mathematics of Computing | 90C25 | Numerical Analysis | Combinatorics | 62L20 | COMPUTER SCIENCE, SOFTWARE ENGINEERING | MATHEMATICS, APPLIED | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | APPROXIMATION ALGORITHMS | COMPOSITE OPTIMIZATION | Methods | Convergence (Social sciences) | Studies | Computer programming | Stochastic models | Nonlinear programming | Policies | Approximation | Mathematical analysis | Programming | Stochasticity | Optimization | Convergence

Journal Article