• Tensorlab

• Referenced in 77 articles [sw14255]
• block term decompositions (BTD) and low multilinear rank approximation (LMLRA), complex optimization: quasi-Newton ... complex variables including numerical complex differentiation, global minimization of bivariate polynomials and rational functions: both ... cumulants, tensor visualization, estimating a tensor’s rank or multilinear rank...

• SLRA

• Referenced in 24 articles [sw11262]
• weighted 2-norm. Backward error minimization and Sylvester low-rank approximation formulations of the problem...

• MSCRA_rankmin

• Referenced in 3 articles [sw37064]
• modeled as a structured rank minimization problem. We reformulate this problem as a mathematical program ... reduction of the error and approximate rank bounds of the first stage convex relaxation...

• TARM

• Referenced in 1 article [sw30728]
• turbo-type algorithm for affine rank minimization. The affine rank minimization (ARM) problem arises ... goal is to recover a low-rank matrix from a small amount of noisy affine...

• DSPCA

• Referenced in 35 articles [sw04804]
• positive, semidefinite symmetric matrix by a rank-one matrix, with an upper bound ... problem. We also discuss Nesterov’s smooth minimization technique applied to the SDP arising...

• MSOPS-II

• Referenced in 13 articles [sw11982]
• significant enhancements allow the new MSOPS-II ranking process to be used as part ... general-purpose multi/many objective optimisation algorithm, requiring minimal initial configuration...

• IML - Integer Matrix Library

• Referenced in 16 articles [sw00440]
• matrix. Certified linear system solving: compute a minimal denominator solution x to a system ... integer matrix with arbitrary shape and rank profile. In addition, IML provides some low level...

• Neurofitter

• Referenced in 14 articles [sw09289]
• error function or fitness function makes the ranking of different parameter sets possible. The second ... find the best parameter set in a minimal amount of time. In this review...

• preCICE

• Referenced in 27 articles [sw08713]
• proven scalability on 10000s of MPI Ranks. The software offers methods for transient equation coupling ... CalculiX, are available. Due to the minimally-invasive approach of preCICE, adapters for in-house...

• RANKBOOST+

• Referenced in 2 articles [sw35566]
• RankBoost designed to minimize a different upper bound on rank loss...

• OEIG

• Referenced in 4 articles [sw07166]
• possible to rank deficient; i.e., we search for λ that locally minimize the smallest singular...

• svt

• Referenced in 1 article [sw37232]
• achieve shrinkage and low rank solutions. To minimize a nuclear norm regularized loss function...

• timma

• Referenced in 1 article [sw17706]
• Inhibition Interaction using Maximization and Minimization Averaging. Prediction and ranking of drug combinations based...

• SBmethod

• Referenced in 12 articles [sw07710]
• Rendl [2000]; Helmberg and Kiwiel [1999] for minimizing the maximum eigenvalue of an affine matrix ... matrices such as sparsity and low rank structure. The code comes with ABSOLUTELY NO WARRANTY...

• GZoltar

• Referenced in 2 articles [sw26885]
• analyzed to both minimize the test suite and return a ranked list of diagnosis candidates...

• PAGE

• Referenced in 7 articles [sw23828]
• method that uses predefined gene sets and ranks of genes to identify significant biological changes ... given microarray data set is minimal or moderate. Results: We developed a modified gene...

• PL-ranking

• Referenced in 2 articles [sw28415]
• ranking loss constraint ignores class information, we further adopt a listwise constraint to minimize ... number of iterations is reduced. Finally, low-rank based regularization is applied to exploit...

• LRIPy

• Referenced in 2 articles [sw26565]
• convex Douglas-Rachford. Purpose: Low-rank rank inducing norms and non-convex Proximal Splitting Algoriths ... attempt to find exact rank/cardinality-r solutions to minimization problems with convex loss functions, i.e., avoiding ... proximal mappings of the low-rank inducing Frobenius and Spectral norms, as well as, their...

• LRINorm

• Referenced in 2 articles [sw26564]
• Convex Proximal Splitting Methods. Low-rank rank inducing norms and non-convex Proximal Splitting Algoriths ... attempt to find exact rank/cardinality-r solutions to minimization problems with convex loss functions, i.e., avoiding ... proximal mappings of the low-rank inducing Frobenius and Spectral norms, as well as, their...

• PAL-Tiling

• Referenced in 2 articles [sw28419]
• objective under convergence guarantees. To simulate the minimization subject to the constraint that the matrices ... enables an automatic determination of the factorization rank...