- Referenced in 124 articles
- Sparse Optimal Control Software (SOCS). The Sparse Optimal Control Family, developed by The Boeing Company ... software packages, available separately or together. Sparse Optimal Control Software (SOCS) is general-purpose software ... include trajectory optimization, chemical process control and machine tool path definition. Sparse Nonlinear Programming exploits ... sparse linear algebra technology to solve very large optimization problems orders of magnitude faster than...
- Referenced in 441 articles
- large-scale optimization system, for the solution of sparse linear and nonlinear programs. The objective...
- Referenced in 419 articles
- structured matrices) sparse s.p.d. linear systems systems of nonlinear equations (including unconstrained optimization) roots ... fast) interval arithmetic for real and complex sparse matrices (very fast) automatic differentiation (forward mode ... systems of nonlinear equations) Hessians (for global optimization) Taylor series for univariate functions automatic slopes...
- Referenced in 61 articles
- SparsePOP: a sparse semidefinite programming relaxation of polynomial optimization problems. SparsePOP is a Matlab implementation ... sparse semidefinite programming (SDP) relaxation method for approximating a global optimal solution of a polynomial ... optimization problem (POP) proposed by Waki et al. . The sparse SDP relaxation exploits ... sparse structure of polynomials in POPs when applying “a hierarchy of LMI relaxations of increasing...
- Referenced in 1626 articles
- banded matrices are handled, but not general sparse matrices. In all areas, similar functionality ... innermost loops. These block operations can be optimized for each architecture to account...
- Referenced in 26 articles
- OSKI: Optimized Sparse Kernel Interface. What is OSKI? The Optimized Sparse Kernel Interface (OSKI) Library...
- Referenced in 236 articles
- sparse or structured matrix. These new algorithms have applications in signal processing, optimization...
- Referenced in 507 articles
- have proved highly effective for solving constrained optimization problems with smooth nonlinear functions ... available and that the constraint gradients are sparse. We discuss an SQP algorithm that uses ... important application is to trajectory optimization in the aerospace industry. Numerical results are given...
- Referenced in 50 articles
- show that when the associated optimization problem is sparse, meaning most gradient updates only modify ... decision variable, then HOGWILD! achieves a nearly optimal rate of convergence. We demonstrate experimentally that...
- Referenced in 617 articles
- development and performance evaluation of sparse matrix algorithms. It allows for robust and repeatable experiments ... that typically do not have such geometry (optimization, circuit simulation, economic and financial modeling, theoretical...
- Referenced in 57 articles
- fast algorithm for sparse reconstruction based on shrinkage, subspace optimization, and continuation. We propose ... recovering sparse solutions to an undetermined system of linear equations Ax=b. The algorithm ... likely to be nonzero in an optimal solution. Restricting the decision variables x to this ... speed and its ability to recover sparse signals...
- Referenced in 36 articles
- algorithms can handle large-scale sparse data. 2) Optimal Convergence Rate. The convergence rate...
- Referenced in 36 articles
- universal functional optimization (UFO) system is an interactive modular system for solving ... both dense medium-size and sparse large-scale optimization problems. The UFO system...
- Referenced in 204 articles
- based on Newton steps on the perturbed optimality system ... matrix A may be either full or sparse; computations are made accordingly. This...
- Referenced in 73 articles
- which yield asymptotic optimality of our estimator for high dimensional but sparse additive models. Finally...
- Referenced in 273 articles
- algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates ... objectives and problems with very noisy and/or sparse gradients. The hyper-parameters have intuitive interpretations ... best known results under the online convex optimization framework. Empirical results demonstrate that Adam works...
- Referenced in 13 articles
- Sparsity: Optimization Framework for Sparse Matrix Kernels. Sparse matrix–vector multiplication is an important computational ... data structure transformations and optimization heuristics that are specific to sparse matrices. It provides ... paper we discuss the optimization of two operations: a sparse matrix times a dense vector ... sparse matrix times a set of dense vectors. Our experience indicates that register level optimizations...
- Referenced in 101 articles
- extensive numerical tests and comparison with other optimization codes are presented. The test examples show ... that PENNON is particularly suitable for large sparse problems...
- Referenced in 11 articles
- modern processors with wide SIMD units. Sparse matrix-vector multiplication (spMVM) is the most time ... processor and accelerator architectures. However, the optimal sparse matrix data storage format is highly hardware...
- Referenced in 15 articles
- solver for large-scale, sparse, nonlinear optimization problems with millions of variables and constraints. Convexity ... designed from its core foundations as a sparse sequential quadratic programming (SQP) / interior-point ... BFGS) update techniques for Hessian approximations, and sparse linear algebra. Furthermore it is based ... design and development philosophy. Two large-scale optimization problems from space applications that demonstrate...