Matrix computations (3rd ed.)
Exploiting sparsity in primal-dual interior-point methods for semidefinite programming
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Free material optimization via mathematical programming
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Interior point algorithms: theory and analysis
Interior point algorithms: theory and analysis
A Note on the Calculation of Step-Lengths in Interior-Point Methods for Semidefinite Programming
Computational Optimization and Applications
Solving Large-Scale Sparse Semidefinite Programs for Combinatorial Optimization
SIAM Journal on Optimization
A Spectral Bundle Method for Semidefinite Programming
SIAM Journal on Optimization
GloptiPoly: Global optimization over polynomials with Matlab and SeDuMi
ACM Transactions on Mathematical Software (TOMS)
Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semidefinite programming for ad hoc wireless sensor network localization
Proceedings of the 3rd international symposium on Information processing in sensor networks
An improved semidefinite programming relaxation for the satisfiability problem
Mathematical Programming: Series A and B
On Extracting Maximum Stable Sets in Perfect Graphs Using Lovász's Theta Function
Computational Optimization and Applications
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Theory of semidefinite programming for Sensor Network Localization
Mathematical Programming: Series A and B
Computing the types of the relationships between autonomous systems
IEEE/ACM Transactions on Networking (TON)
SpaseLoc: An Adaptive Subproblem Algorithm for Scalable Wireless Sensor Network Localization
SIAM Journal on Optimization
New code upper bounds from the Terwilliger algebra and semidefinite programming
IEEE Transactions on Information Theory
Semidefinite Programming Heuristics for Surface Reconstruction Ambiguities
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
k-Clustering Minimum Biclique Completion via a Hybrid CP and SDP Approach
CPAIOR '09 Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Interior-Point Method for Nuclear Norm Approximation with Application to System Identification
SIAM Journal on Matrix Analysis and Applications
On the generation of positivstellensatz witnesses in degenerate cases
ITP'11 Proceedings of the Second international conference on Interactive theorem proving
ACM Transactions on Mathematical Software (TOMS)
An efficient framework for passive compact dynamical modeling of multiport linear systems
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
Fair scheduling of bag-of-tasks applications using distributed Lagrangian optimization
Journal of Parallel and Distributed Computing
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DSDP implements the dual-scaling algorithm for semidefinite programming. The source code for this interior-point algorithm, written entirely in ANSI C, is freely available under an open source license. The solver can be used as a subroutine library, as a function within the Matlab environment, or as an executable that reads and writes to data files. Initiated in 1997, DSDP has developed into an efficient and robust general-purpose solver for semidefinite programming. Its features include a convergence proof with polynomially bounded worst-case complexity, primal and dual feasible solutions when they exist, certificates of infeasibility when solutions do not exist, initial points that can be feasible or infeasible, relatively low memory requirements for an interior-point method, sparse and low-rank data structures, extensibility that allows applications to customize the solver and improve its performance, a subroutine library that enables it to be linked to larger applications, scalable performance for large problems on parallel architectures, and a well-documented interface and examples of its use. The package has been used in many applications and tested for efficiency, robustness, and ease of use.