Results 61 to 70 of about 244,754 (100)

Weighted nonnegative tensor factorization: on monotonicity of multiplicative update rules and application to user-guided audio source separation

open access: yes, 2013
This report focuses on so-called weighted variants of nonnnegative matrix factorization (NMF) and more generally nonnnegative tensor factorization (NTF) approximations. First, we consider multiplicative update (MU) rules to optimize these approximations,
Chevallier, Louis   +2 more
core  

Limestone: high-throughput candidate phenotype generation via tensor factorization. [PDF]

open access: yesJ Biomed Inform, 2014
Ho JC   +6 more
europepmc   +1 more source

Peak picking NMR spectral data using non-negative matrix factorization. [PDF]

open access: yesBMC Bioinformatics, 2014
Tikole S   +4 more
europepmc   +1 more source

Munc13-1 couples DAG and Ca<sup>2+</sup> signaling to dynamic vesicle priming, synaptic short-term plasticity, and posttetanic potentiation. [PDF]

open access: yesSci Adv
Ranjan M   +10 more
europepmc   +1 more source

Advances in nonnegative matrix and tensor factorization. [PDF]

open access: yesComput Intell Neurosci, 2008
Cichocki A   +4 more
europepmc   +1 more source

Audio source separation usinga redundant library of source spectral bases for nonnegative tensor factorization

open access: yes, 2015
This work proposes a solution to the problem of under-determined audio source separation using pre-trained redundant source-based prior information.
Svaizer, Piergiorgio   +2 more
core  

HYPERSPECTRAL AUTOFLUORESCENCE IMAGING OF DRUSEN AND RETINAL PIGMENT EPITHELIUM IN DONOR EYES WITH AGE-RELATED MACULAR DEGENERATION. [PDF]

open access: yesRetina, 2016
Tong Y   +8 more
europepmc   +1 more source

Interpretable and Federated Tensor Factorization for Computational Phenotyping

open access: yes, 2017
DoctorPhenotyping based on machine learning has been proposed to facilitate extraction of meaningful phenotypes automatically from electronic health records (EHRs) without human supervision through a process called computational phenotyping.
김예진
core  

Probabilistic latent variable models as nonnegative factorizations. [PDF]

open access: yesComput Intell Neurosci, 2008
Shashanka M, Raj B, Smaragdis P.
europepmc   +1 more source

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