Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	785328
MD5	3F500F92D9DD29738D5874821C0006A3
PackageDescription	Software for Semidefinite Programming The DSDP software is a free open source implementation of an interior-point method for semidefinite programming. It provides primal and dual solutions, exploits low-rank structure and sparsity in the data, and has relatively low memory requirements for an interior-point method. It allows feasible and infeasible starting points and provides approximate certificates of infeasibility when no feasible solution exists. The dual-scaling algorithm implemented in this package has a convergence proof and worst-case polynomial complexity under mild assumptions on the data. Furthermore, the solver offers scalable parallel performance for large problems and a well documented interface. Some of the most popular applications of semidefinite programming and linear matrix inequalities (LMI) are model control, truss topology design, and semidefinite relaxations of combinatorial and global optimization problems. . This package contains the documentation and examples.
PackageMaintainer	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	dsdp-doc
PackageSection	doc
PackageVersion	5.8-5
SHA-1	0046399F3CA144336313A066FF029964D5CF2B80
SHA-256	C22C0B0F9CBE888956A18E3E58A1B14C03D8212CCBBAA89A17DAF69B49529B31

Key	Value
FileSize	785296
MD5	D8231A84F6931C590AE3C86A19BBDC92
PackageDescription	Software for Semidefinite Programming The DSDP software is a free open source implementation of an interior-point method for semidefinite programming. It provides primal and dual solutions, exploits low-rank structure and sparsity in the data, and has relatively low memory requirements for an interior-point method. It allows feasible and infeasible starting points and provides approximate certificates of infeasibility when no feasible solution exists. The dual-scaling algorithm implemented in this package has a convergence proof and worst-case polynomial complexity under mild assumptions on the data. Furthermore, the solver offers scalable parallel performance for large problems and a well documented interface. Some of the most popular applications of semidefinite programming and linear matrix inequalities (LMI) are model control, truss topology design, and semidefinite relaxations of combinatorial and global optimization problems. . This package contains the documentation and examples.
PackageMaintainer	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	dsdp-doc
PackageSection	doc
PackageVersion	5.8-4
SHA-1	FA9697B303E8C3921CD580AFE53113904C854D84
SHA-256	3147CEACA8842266EF366B96A137A1A4A532435B4B2F4217B09B5495F34E4F74