Sentence examples for matrix factorization procedure from inspiring English sources

In the high-level layer, we use the NMF (Non-negative Matrix Factorization) procedure which has been demonstrated to be an effective approach for word learning.

This is done using the same matrix factorization procedure as before with the only difference that the basis vectors matrix is kept fixed and only the activation matrix is calculated.

Our algorithm is based on a modified non-negative matrix factorization (NMF) procedure that no labeled data is required to distinguish between percussive and harmonic bases because information from percussive and harmonic sounds is integrated into the decomposition process.

To achieve this, we design a new matrix factorization objective function and incorporate a label matrix factorization term as well as a network regularization term into it.

AXIOME also implements features including the PAired-eND Assembler for Illumina sequences (PANDAseq), non-negative matrix factorization (NMF), multi-response permutation procedures (MRPP), exploring and recovering phylogenetic novelty (SSUnique) and indicator species analysis.

Section 5 describes the procedure for non-negative matrix factorization of reverberant speech.

We used nonnegative matrix factorization (NMF) method, more specifically the metagene projection procedure as proposed by Tamayo et al. [9].

The redundant information and measuring errors in the pre-determined petroleum fraction samples are eliminated through the procedure of calculating the basis fractions with non-negative matrix factorization (NMF) algorithm, meanwhile the scale of the feedstock database is highly decreased.

This algorithm is based on a modified genomic Non-negative Matrix Factorization (gNMF) algorithm and includes several additional components, namely a pilot hierarchical clustering procedure to determine the number of clusters, a multiple random initiation scheme, a new stop criterion for the core gNMF, as well as a 10-fold cross-validation stability test for quality assessment.

The identification of clusters is cast as a Boolean matrix factorization problem over the interaction matrix between trans-factors and mRNAs.

Nonnegative Matrix Factorization Nonnegative matrix factorization (NMF) is a mathematical approach that factorizes or decomposes a complex multidimensional data set in order to identify defining underlying signatures that make up the pooled data set.