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A Multilinear Singular Value Decomposition
TLDR
There is a strong analogy between several properties of the matrix and the higher-order tensor decomposition; uniqueness, link with the matrix eigenvalue decomposition, first-order perturbation effects, etc., are analyzed. Expand
Subspace Identification for Linear Systems: Theory ― Implementation ― Applications
TLDR
This book focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finitedimensional dynamical systems, which allow for a fast, straightforward and accurate determination of linear multivariable models from measured inputoutput data. Expand
Assessing computational tools for the discovery of transcription factor binding sites
TLDR
The purpose of the current assessment is to provide some guidance to users regarding the accuracy of currently available tools in various settings, and to provide a benchmark of data sets for assessing future tools. Expand
On the Best Rank-1 and Rank-(R1 , R2, ... , RN) Approximation of Higher-Order Tensors
TLDR
A multilinear generalization of the best rank-R approximation problem for matrices, namely, the approximation of a given higher-order tensor, in an optimal least-squares sense, by a tensor that has prespecified column rank value, rowRank value, etc. Expand
N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems
TLDR
Two new N4SID algorithms to identify mixed deterministic-stochastic systems are derived and these new algorithms are compared with existing subspace algorithms in theory and in practice. Expand
Gene prioritization through genomic data fusion
TLDR
A bioinformatics approach, together with a freely accessible, interactive and flexible software termed Endeavour, to prioritize candidate genes underlying biological processes or diseases, based on their similarity to known genes involved in these phenomena, offers an alternative integrative method for gene discovery. Expand
Least Squares Support Vector Machines
Support Vector Machines Basic Methods of Least Squares Support Vector Machines Bayesian Inference for LS-SVM Models Robustness Large Scale Problems LS-SVM for Unsupervised Learning LS-SVM forExpand
BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis
TLDR
The biomaRt package provides a tight integration of large, public or locally installed BioMart databases with data analysis in Bioconductor creating a powerful environment for biological data mining. Expand
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