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Our approach is based on supervised learning and dimensionality reduction techniques that allow the representation of high dimensional nonlinear actions to linear latent low dimensional spaces.
We will test the self-care support program's effect, both overall and in the latent low and high function response groups, as predicted by baseline characteristics on post-TKR 6 and 12 month functional outcome.
We have incorporated into the revised Discussion section statements regarding the possibility that the residual sensitivity of channels bearing these potent mutations may derive from a latent low affinity site(s).
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MF [4] projects users and items into a latent low-dimensional space.
The method is called latent low-rank representation (LatLRR), which is an improvement of LRR.
We referred to the proposed method as SRC-based latent low-rank representation (SRC- LatLRR).
Latent low-rank representation is an extension of low-rank representation.
We firstly review SRC and latent low-rank representation methods in Sections 2.1 and 2.2, respectively.
To reduce noise [ 19– 21] and get salient features [ 20] for tumor classification, in this paper, we introduce latent low-rank representation to preprocess gene expression data.
Our method can be seen as the combination of SRC [ 17] and latent low-rank representation for feature extraction [ 20], so we named it as SRC-LatLRR.
In the proposed method, we firstly use latent low-rank representation for extracting salient features and removing noise from the original samples data.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com