• SDPT3

  • Referenced in 630 articles [sw04009]
  • structure are exploited. We also exploit low-rank structures in the constraint matrices associated...
  • SVMlight

  • Referenced in 261 articles [sw04076]
  • problem of learning a ranking function. The optimization algorithms used in SVMlight are described ... this version is an algorithm for learning ranking functions [Joachims, 2002c]. The goal ... objects as accurately as possible. Such ranking problems naturally occur in applications like search engines...
  • UTV

  • Referenced in 238 articles [sw05213]
  • Expansin pack: Special-purpose rank-revealing algorithms. This collection of Matlab 7.0 software supplements ... includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original ... provide algorithms for computing and modifying symmetric rank-revealing VSV decompositions, we expand the algorithms ... handle interference-type problems with a rank-deficient covariance matrix, and we provide a robust...
  • ScaLAPACK

  • Referenced in 404 articles [sw00830]
  • Cholesky factorization, matrix inversion, full-rank linear least squares problems, orthogonal and generalized orthogonal factorizations...
  • CP-nets

  • Referenced in 135 articles [sw01374]
  • nets, and how to merge these sub-rankings derived from the chain CP-nets ... generate the preference ranking of the tree-structured CP-net. At last, the corresponding analysis...
  • VisualUTA

  • Referenced in 106 articles [sw16231]
  • Ordinal regression revisited: multiple criteria ranking with a set of additive value functions. VisualUTA ... method for multiple criteria ranking of alternatives from set A using a set of additive ... necessary (strong) and a possible (weak) ranking of alternatives from A, being, respectively, a partial...
  • SDPLR

  • Referenced in 119 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...
  • TensorToolbox

  • Referenced in 153 articles [sw04185]
  • expressed as the sum of rank-1 tensors. We are interested in the case where...
  • VGAM

  • Referenced in 93 articles [sw04490]
  • additive models, and associated models (Reduced-Rank VGLMs, Quadratic RR-VGLMs, Reduced-Rank VGAMs). This...
  • ELECTRE

  • Referenced in 122 articles [sw02971]
  • according to the three main problematics: choosing, ranking and sorting. The fourth section presents...
  • MADM

  • Referenced in 121 articles [sw06484]
  • Rangiranje (VIKOR), Data Envelopment Analysis (DEA), Preference Ranking METHod for Enrichment Evaluations (PROMETHEE), ELimination...
  • Manopt

  • Referenced in 87 articles [sw08493]
  • manifolds is well-suited to deal with rank and orthogonality constraints. Such structured constraints appear ... pervasively in machine learning applications, including low-rank matrix completion, sensor network localization, camera network...
  • CMA-ES

  • Referenced in 106 articles [sw05063]
  • underlying objective function are made. Only the ranking between candidate solutions is exploited for learning...
  • OSL

  • Referenced in 106 articles [sw09295]
  • than those assumed in simplex implementations. Severe rank deficiency must also be accommodated, making...
  • FRK

  • Referenced in 93 articles [sw19172]
  • package FRK. Fixed Rank Kriging is a tool for spatial/spatio-temporal modelling and prediction with large...
  • Tensorlab

  • Referenced in 53 articles [sw14255]
  • block term decompositions (BTD) and low multilinear rank approximation (LMLRA), complex optimization: quasi-Newton ... cumulants, tensor visualization, estimating a tensor’s rank or multilinear rank...
  • testmatrix

  • Referenced in 79 articles [sw14347]
  • inverses or known eigenvalues; ill-conditioned or rank deficient matrices; and symmetric, positive definite, orthogonal...
  • MUSCLE

  • Referenced in 71 articles [sw13193]
  • MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets...
  • CirCut

  • Referenced in 42 articles [sw04782]
  • Rank-two relaxation heuristics for MAX-CUT and other binary quadratic programs The Goemans--Williamson ... better practical performance, we propose an alternative, rank-two relaxation and develop a specialized version ... problem.par A computer code based on the rank-two relaxation heuristics is compared with...
  • softImpute

  • Referenced in 63 articles [sw12263]
  • columns or both, and for computing low-rank SVDs on large sparse centered matrices...