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Robust Low-Rank Tensor Decomposition with the L 2 Criterion
The growing prevalence of tensor data, or multiway arrays, in science and engineering applications motivates the need for tensor decompositions that are robust against outliers. In this article, we pr
DataCite Commons2024-02-06 更新380
Optimal Sparse Singular Value Decomposition for High-Dimensional High-Order Data
In this article, we consider the sparse tensor singular value decomposition, which aims for dimension reduction on high-dimensional high-order data with certain sparsity structure. A method named spar
DataCite Commons2021-09-29 更新60
Additional file 11 of "WormTensor: a clustering method for time-series whole-brain activity data of C. elegans"
P-values of Hypergeometric test and q-value of FDR of all the clustering methods with the optimal numbers of clusters
Figshare2022-12-15 更新50
Generalized tensor decomposition with features on multiple modes
Higher-order tensors have received increased attention across science and engineering. While most tensor decomposition methods are developed for a single tensor observation, scientific studies often c
DataCite Commons2021-10-25 更新80
Additional file 4: of Predicting clinically promising therapeutic hypotheses using tensor factorization
Results of benchmark experiments. (XLSX 11 kb)
DataCite Commons2020-08-27 更新60
