• SDPT3

  • Referenced in 522 articles [sw04009]
  • problems in either SDPA or SeDuMi format. Sparsity and block diagonal structure are exploited...
  • PHCpack

  • Referenced in 181 articles [sw00705]
  • polynomial system, in particular its sparsity. In this paper the structure and design...
  • CSDP

  • Referenced in 178 articles [sw00169]
  • systems, and it makes effective use of sparsity in the constraint matrices. CSDP has been...
  • SDPA

  • Referenced in 150 articles [sw03275]
  • interior-point method. It fully exploits the sparsity of given problems. There are some variants...
  • SuperLU

  • Referenced in 136 articles [sw00930]
  • user supplied routines. This preordering for sparsity is completely separate from the factorization. Working precision...
  • ve08

  • Referenced in 131 articles [sw05141]
  • structure. This structure is always implied by sparsity of G, and depends only...
  • hgam

  • Referenced in 73 articles [sw11201]
  • dimensional Additive Modelling. We propose a new sparsity-smoothness penalty for high-dimensional generalized additive ... models. The combination of sparsity and smoothness is crucial for mathematical theory as well ... models. Finally, an adaptive version of our sparsity-smoothness penalized approach yields large additional performance...
  • TAF

  • Referenced in 74 articles [sw07492]
  • reverse mode of AD and Automatic Sparsity Detection (ASD) for detection of the sparsity structure...
  • SoPlex

  • Referenced in 82 articles [sw04063]
  • simplex algorithm. It features preprocessing techniques, exploits sparsity, and offers primal and dual solving routines...
  • SuperLU-DIST

  • Referenced in 69 articles [sw00002]
  • user supplied routines. This preordering for sparsity is completely separate from the factorization. Working precision...
  • SFSDP

  • Referenced in 30 articles [sw04793]
  • FSDP, SFSDP exploits the aggregated and correlative sparsity of a sensor network localization problem...
  • COLAMD

  • Referenced in 26 articles [sw00145]
  • sparse partial pivoting, which requires a sparsity preserving column pre-ordering prior to numerical factorization...
  • ADMAT

  • Referenced in 26 articles [sw04864]
  • employs many sophisticated techniques such as exploiting sparsity and structure to achieve high efficiency...
  • SSS

  • Referenced in 24 articles [sw07794]
  • priors over the model space that induce sparsity and parsimony over and above the traditional...
  • ParaSails

  • Referenced in 24 articles [sw11521]
  • compute a sparse approximate inverse. The sparsity pattern used is the pattern of a power...
  • BLOOMP

  • Referenced in 16 articles [sw06454]
  • four performance metrics: dynamic range, noise stability, sparsity, and resolution. With respect to dynamic range ... best performer. With respect to sparsity, BLOOMP is the best performer for high dynamic range...
  • DAEPACK

  • Referenced in 16 articles [sw12958]
  • automatically generate new code which determines the sparsity pattern of the model for a given ... inputs (sparsity pattern generation), automatic generation of a discontinuity-locked model and extraction of hidden...
  • Sparsity

  • Referenced in 12 articles [sw08686]
  • Sparsity: Optimization Framework for Sparse Matrix Kernels. Sparse matrix–vector multiplication is an important computational ... zero structure of the matrix. The SPARSITY system is designed to address these problems ... tuned to their matrices and machines. SPARSITY combines traditional techniques such as loop transformations with...
  • ADMIT

  • Referenced in 21 articles [sw02687]
  • differentiated, ADMIT-1 will exploit sparsity if present to yield sparse derivative matrices (in sparse...
  • SparseFIS

  • Referenced in 10 articles [sw13736]
  • Data-Driven Learning of Fuzzy Systems With Sparsity Constraints. n this paper, we deal with ... least-squares error measure by applying a sparsity-constrained steepest descent-optimization procedure. Depending ... sparsity threshold, weights of many or a few rules can be forced toward 0, thereby ... linear consequent parameters by a regularized sparsity-constrained-optimization procedure for each rule separately (local...