• LAPACK

  • Referenced in 1648 articles [sw00503]
  • estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices...
  • MINOS

  • Referenced in 442 articles [sw05095]
  • sparse LU factors of the basis matrix), automatic scaling of linear contraints, and automatic estimation...
  • spcov

  • Referenced in 36 articles [sw12271]
  • spcov: Sparse Estimation of a Covariance Matrix. Provides a covariance estimator for multivariate normal data ... Bien, J., and Tibshirani, R. (2011), ”Sparse Estimation of a Covariance Matrix,” Biometrika...
  • LSQR

  • Referenced in 372 articles [sw00530]
  • where the matrix A is large and sparse. The method is based on the bidiagonalization ... Reliable stopping criteria are derived, along with estimates of standard errors...
  • hgam

  • Referenced in 73 articles [sw11201]
  • asymptotic optimality of our estimator for high dimensional but sparse additive models. Finally, an adaptive...
  • elasticnet

  • Referenced in 14 articles [sw08181]
  • package elasticnet: Elastic-Net for Sparse Estimation and Sparse PCA. This package provides functions ... also provides functions for estimating sparse Principal Components. The Lasso solution paths can be computed...
  • flare

  • Referenced in 19 articles [sw12406]
  • SQRT Lasso, Lq Lasso for estimating high dimensional sparse linear model. We adopt the alternating ... further acceleration. Besides the sparse linear model estimation, we also provide the extension of these ... Lasso variants to sparse Gaussian graphical model estimation including TIGER and CLIME using either ... computation is memory-optimized using the sparse matrix output...
  • camel

  • Referenced in 10 articles [sw14318]
  • Lasso and Calibrated Dantzig Selector for estimating sparse linear models; (2) Calibrated Multivariate Regression ... estimating sparse multivariate linear models; (3) Tiger, Calibrated Clime for estimating sparse Gaussian graphical models...
  • Adam

  • Referenced in 400 articles [sw22205]
  • stochastic objective functions, based on adaptive estimates of lower-order moments. The method is straightforward ... objectives and problems with very noisy and/or sparse gradients. The hyper-parameters have intuitive interpretations...
  • QUIC

  • Referenced in 25 articles [sw11795]
  • QUIC: quadratic approximation for sparse inverse covariance estimation. The ℓ 1 -regularized Gaussian maximum likelihood ... estimator (MLE) has been shown to have strong statistical guarantees in recovering a sparse inverse...
  • softImpute

  • Referenced in 63 articles [sw12263]
  • with the current estimate. For large matrices there is a special sparse-matrix class named...
  • SuperLU

  • Referenced in 179 articles [sw00930]
  • library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high ... also provided to equilibrate the system, estimate the condition number, calculate the relative backward error...
  • sparseLM

  • Referenced in 5 articles [sw04810]
  • sparseLM : Sparse Levenberg-Marquardt nonlinear least squares in C/C++ Several estimation problems in vision involve ... parameters to be estimated, which leads to minimization problems possessing a sparse structure. Taking advantage ... this sparseness during minimization is known to achieve enormous computational savings. Nevertheless, since the underlying ... results from its application to important sparse estimation problems in geometric vision...
  • FASTCLIME

  • Referenced in 12 articles [sw10889]
  • linear programming and large-scale precision matrix estimation in R. We develop an R package ... implement an important sparse precision matrix estimation method called CLIME (Constrained L 1 Minimization Estimator...
  • SuperLU-DIST

  • Referenced in 87 articles [sw00002]
  • library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high ... also provided to equilibrate the system, estimate the condition number, calculate the relative backward error...
  • msgl

  • Referenced in 10 articles [sw26552]
  • regression with sparse group lasso penalty. Simultaneous feature selection and parameter estimation for classification. Suitable ... algorithm computes the sparse group lasso penalized maximum likelihood estimate. Use of parallel computing...
  • SVMlight

  • Referenced in 262 articles [sw04076]
  • they are conservatively biased. Almost unbiased estimates provides leave-one-out testing. SVMlight exploits that ... applications. Many tasks have the property of sparse instance vectors. This implementation makes...
  • TAUCS

  • Referenced in 31 articles [sw04014]
  • Matrix Input/Output. Routines to read and write sparse matrices using a simple file format with ... wall-clock and CPU time), physical-memory estimator, and logging...
  • PSICOV

  • Referenced in 5 articles [sw17010]
  • precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments. Motivation ... which introduces the use of sparse inverse covariance estimation to the problem of protein contact...
  • admixture

  • Referenced in 6 articles [sw26449]
  • implementation of ADMIXTURE that computes maximum-likelihood estimates of the admixture proportions and population allele ... optimization (M-step) that encourages sparse admixture estimates. This code was tested using R version...