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- programs on both a small and large scale. Python supports multiple programming paradigms, including object ... automatic memory management and has a large and comprehensive standard library. Python interpreters are available...
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- Fortran77 subroutines designed to solve large scale eigenvalue problems. The package is designed to compute ... matrix A. It is most appropriate for large sparse or structured matrices A where structured ... technique that is suitable for large scale problems. For many standard problems, a matrix factorization ... ARPACK software is capable of solving large scale symmetric, nonsymmetric, and generalized eigenproblems from significant...
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- building blocks for the implementation of large-scale application codes on parallel (and serial) computers...
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- BFGS-B Fortran subroutines for large-scale bound-constrained optimization. L-BFGS...
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- software package for large-scale nonlinear optimization. It is designed to find (local) solutions...
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- SNOPT: An SQP algorithm for large-scale constrained optimization. Sequential quadratic programming (SQP) methods have...
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- built-in eigs routine (ARPACK) for large-scale eigenvalue computations...
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- LANCELOT. A Fortran package for large-scale nonlinear optimization (Release A). LANCELOT is a software ... package for solving large-scale nonlinear optimization problems. This book provides a coherent overview ... design and implementation of large-scale optimization algorithms...
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- MINOS is a large-scale optimization system, for the solution of sparse linear and nonlinear...
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- improved to meet the demands of large-scale applications. Nuprl LPE, the newest release, features...
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- BFGS-B Fortran subroutines for large-scale bound-constrained optimization L-BFGS...
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- apparent. It is not intended for large-scale problems...
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- state-of-the-art packages for large-scale scientific computation written and developed...
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- SPGL1: A solver for large-scale sparse reconstruction: Probing the Pareto frontier for basis pursuit ... suitable for problems that are large scale and for those that are in the complex ... problems demonstrate that the method scales well to large problems...
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- version includes an algorithm for training large-scale transductive SVMs. The algorithm proceeds by solving ... code has been used on a large range of problems, including text classification [Joachims, 1999c...
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- parallel programming model initially developed for large-scale web content processing. Data analysis meets ... calculation over extremely large datasets. The arrival of MapReduce provides a chance to utilize commodity...
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- deployed on mainframe computers, such as large-scale batch and transaction processing jobs...
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- reduced-gradient (GRG) algorithm for solving large-scale nonlinear programs involving sparse nonlinear constraints ... very competitive with other codes for large-scale nonlinear programming from both an efficiency...
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- versatile environment for testing small- and large-scale nonlinear optimization algorithms. Although many of these...
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- either SCILAB or matlab for solving large scale linear programming problems. It can be freely...