• SDPT3

  • Referenced in 652 articles [sw04009]
  • structure are exploited. We also exploit low-rank structures in the constraint matrices associated...
  • SDPLR

  • Referenced in 126 articles [sw04745]
  • based on the idea of low-rank factorization. A specialized version of SDPLR is also ... Programming Algorithm for Semidefinite Programs via Low-rank Factorization” written by S. Burer and R.D.C...
  • Manopt

  • Referenced in 105 articles [sw08493]
  • pervasively in machine learning applications, including low-rank matrix completion, sensor network localization, camera network...
  • softImpute

  • Referenced in 65 articles [sw12263]
  • columns or both, and for computing low-rank SVDs on large sparse centered matrices...
  • LOBPCG

  • Referenced in 32 articles [sw09638]
  • Preconditioned low-rank methods for high-dimensional elliptic PDE eigenvalue problems. We consider elliptic ... desired solution vector x in a low-rank tensor format. In this paper ... hierarchical Tucker decomposition to develop a low-rank variant of LOBPCG, a classical preconditioned eigenvalue ... MALS with LOBPCG and with our low-rank variant is proposed. A number of numerical...
  • ADMiRA

  • Referenced in 31 articles [sw31664]
  • address compressed sensing of a low-rank matrix posing the inverse problem as an approximation ... sparse vector and a low-rank matrix and extending efficient greedy algorithms from the vector ... from the sparse vector to the low-rank matrix case. The performance guarantee is given ... case of noisy measurements and approximately low-rank solution. With a sparse measurement operator...
  • RTRMC

  • Referenced in 36 articles [sw20435]
  • RTRMC : Low-rank matrix completion via preconditioned optimization on the Grassmann manifold. We address ... problem of recovering large matrices of low rank when most of the entries are unknown ... exploit the geometry of the low-rank constraint to recast the problem as an unconstrained...
  • ALEA

  • Referenced in 51 articles [sw10167]
  • python framework for spectral methods and low-rank approximations in uncertainty quantification. ALEA is intended...
  • UQLab

  • Referenced in 33 articles [sw19740]
  • expansions, Gaussian process modelling, a.k.a. Kriging, low-rank tensor approximations), rare event estimation (structural reliability...
  • STRUMPACK

  • Referenced in 32 articles [sw17483]
  • both dense and sparse systems using low-rank structured factorization with randomized sampling...
  • NeNMF

  • Referenced in 31 articles [sw17586]
  • matrix by the product of two low-rank nonnegative matrix factors. It has been widely...
  • NLEIGS

  • Referenced in 29 articles [sw22547]
  • target set, and it also features low-rank approximation techniques for increased computational efficiency. Small...
  • DSDP5

  • Referenced in 27 articles [sw04411]
  • interior-point method, sparse and low-rank data structures, extensibility that allows applications to customize...
  • OptShrink

  • Referenced in 15 articles [sw33657]
  • OptShrink: an algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular ... data-driven algorithm for denoising a low-rank signal matrix buried in noise. It takes ... matrix, an estimate of the signal matrix rank and returns as an output the improved ... black-box manner wherever improving low-rank matrix estimation is desirable. The algorithm outperforms...
  • SLRA

  • Referenced in 24 articles [sw11262]
  • norm. Backward error minimization and Sylvester low-rank approximation formulations of the problem are solved...
  • JIVE

  • Referenced in 14 articles [sw09511]
  • decomposition consists of three terms: a low-rank approximation capturing joint variation across data types ... low-rank approximations for structured variation individual to each data type, and residual noise. JIVE...
  • Algorithm 844

  • Referenced in 17 articles [sw04407]
  • required to obtain a reduced rank approximation to a sparse matrix A. Unfortunately, the approximations ... algorithm, to obtain two kinds of low-rank approximations. The first, the SPQR, approximation...
  • Algorithm 971

  • Referenced in 9 articles [sw22686]
  • intense development of randomized methods for low-rank approximation. These methods target principal component analysis ... several tests, the randomized algorithms for low-rank approximation outperform or at least match...
  • SymNMF

  • Referenced in 12 articles [sw12668]
  • SymNMF: nonnegative low-rank approximation of a similarity matrix for graph clustering. Nonnegative matrix factorization...
  • Colibri

  • Referenced in 8 articles [sw12043]
  • large static and dynamic graphs. Low-rank approximations of the adjacency matrix of a graph ... desirable to track the low-rank structure as the graph evolves over time, efficiently...