- Referenced in 119 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 440 articles
- large-scale optimization system, for the solution of sparse linear and nonlinear programs. The objective...
- Referenced in 406 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 60 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 1582 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 492 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 219 articles
- sparse or structured matrix. These new algorithms have applications in signal processing, optimization...
- Referenced in 586 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 38 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 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 34 articles
- algorithms can handle large-scale sparse data. 2) Optimal Convergence Rate. The convergence rate...
- Referenced in 73 articles
- which yield asymptotic optimality of our estimator for high dimensional but sparse additive models. Finally...
- Referenced in 193 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 34 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 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...
- Referenced in 17 articles
- Lasso, Lq Lasso for estimating high dimensional sparse linear model. We adopt the alternating direction ... method of multipliers and convert the original optimization problem into a sequential L1 penalized least ... adopted for further acceleration. Besides the sparse linear model estimation, we also provide the extension ... CLIME. The computation is memory-optimized using the sparse matrix output...