Sentence examples for based on matrix factorization from inspiring English sources

An extensive amount of research has been done to increase the quality of such predictions, currently the methods based on matrix factorization are recognized as one of the most efficient.

All approximations were given fast algorithms based on matrix factorization methods.

There is a popular approach in recommendation systems which is based on matrix factorization [12].

We have presented a novel approach to solve the EEG inverse problem, which is based on matrix factorization and regularization.

In order to do so, we propose a new method based on matrix factorization and regularization, with the aim of recovering the latent structure of the BES matrix.

In this study, we have presented a novel approach based on matrix factorization techniques to improve the reliability of spectrum sensing significantly by eliminating AGC noise.

A methodology, based on matrix-factorization, is described to transform the discrete model into a family of models corresponding to weightless and unloaded clamped-free (WUCF) columns, each with a transverse vibration spectrum isospectral to the original model.

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles.

In this paper, we propose four multilayer network embedding algorithms based on Nonnegative Matrix Factorization (NMF) with consideration given to four structural properties: whole network (NNMF), community (CNMF), degree distribution (DNMF), and max spanning tree (TNMF).

In our work, we suggest a new model for scale-free networks generation, which is based on the matrix factorization and has a geographical interpretation.

In the model of Zhao et al. [24], two social factors, interpersonal rating behavior similarity and interpersonal interest similarity, are fused into a consolidated personalized recommendation model based on probabilistic matrix factorization.