• # TensorToolbox

• Referenced in 173 articles [sw04185]
• Efficient MATLAB computations with sparse and factored tensors. The term tensor refers simply ... tensor decomposition algorithms. Second, we study factored tensors, which have the property that they ... core tensor (which itself may be dense, sparse, or factored) and a matrix along each...
• # TKPSVD

• Referenced in 11 articles [sw28028]
• combination of tensor Kronecker products with an arbitrary number of d factors A=∑Rj=1σjA ... matrix Kronecker product to tensors such that each factor A(i)j in the TKPSVD ... that for many different structured tensors, the Kronecker product factors ... introduce the new notion of general symmetric tensors, which includes many different structures such...
• # SPLATT

• Referenced in 6 articles [sw30093]
• tools for sparse tensor factorization. SPLATT has a fast, parallel method of multiplying a matricide ... which is a key kernel in tensor factorization methods. SPLATT uses a novel data structure...
• # DFacTo

• Referenced in 6 articles [sw31258]
• DFacTo: Distributed Factorization of Tensors. We present a technique for significantly speeding up Alternating Least ... widely used algorithms for tensor factorization. By exploiting properties of the Khatri-Rao product ... million x 1.5 million dimensional tensor with 1.2 billion non-zero entries...
• # Turbo-SMT

• Referenced in 3 articles [sw35620]
• Turbo-SMT: parallel coupled sparse matrix-tensor factorizations and applications. How can we correlate ... many settings of the Coupled Matrix-Tensor Factorization (CMTF) problem. Can we enhance any CMTF ... nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along...
• # RTNI

• Referenced in 4 articles [sw28081]
• unitaries may be subdivided into arbitrary tensor factors, with dimensions treated symbolically. The algorithm implements ... calculus and produces a weighted sum of tensor networks representing the average over the unitary...
• # Rubik

• Referenced in 1 article [sw30094]
• Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics. Computational phenotyping ... propose Rubik, a constrained non-negative tensor factorization and completion method for phenotyping. Rubik incorporates ... overlapping phenotypes. Rubik also has built-in tensor completion that can significantly alleviate the impact ... Method of Multipliers (ADMM) framework to tensor factorization and completion, which can be easily scaled...
• # Algorithm 738

• Referenced in 7 articles [sw08077]
• software package for unconstrained optimization using tensor methods. This paper describes a software package ... storing one n × n matrix, and factoring it at each iteration, is acceptable. The software ... user to choose between a recently developed “tensor method” for unconstrained optimization and an analogous...
• # SimTensor

• Referenced in 0 articles [sw18210]
• Tucker structure) for reproducible research on tensor factorization algorithms. SimTensor is a stand-alone application ... wide range of facilities for generating tensor data with various configurations. It comes with...
• # SupCP

• Referenced in 1 article [sw24588]
• describe a probabilistic PARAFAC/CANDECOMP (CP) factorization for multiway (i.e., tensor) data that incorporates auxiliary covariates ... based latent variable representation of the CP factorization, in which the latent variables are informed...
• # Algorithm 739

• Referenced in 4 articles [sw04404]
• software package for unconstrained optimization using tensor methods This paper describes a software package ... storing one $n imes n$ matrix, and factoring it at each iteration, is acceptable ... user to choose between a recently developed “tensor method” for unconstrained optimization and an analogous...
• # Package-X

• Referenced in 13 articles [sw18225]
• described. Package-X computes arbitrarily high rank tensor integrals with up to three propagators ... facilitate the computation of fermion form factors at one-loop. The package is intended...