GitHub

non-negative-matrix-factorization

Python PyTorch (GPU) and NumPy (CPU)-based port of Févotte and Dobigeon's robust-NMF algorithm appearing in "Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization." ...
GitHub

non-negative-matrix-factorization

Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the ...
LinkedIn

How do you deploy and update matrix factorization models in production environments?

The first step is to choose a suitable framework for implementing and training your matrix factorization model. There are many frameworks available, such as TensorFlow, PyTorch, Scikit-Learn, or ...
Nature

Deep maximum margin matrix factorization

Collaborative filtering (CF) over ordinal feedback is naturally organized as a problem of matrix completion, where the input consists of a partially observed user-item interaction matrix. Maximum ...
LinkedIn

Python TensorLab: Tensor Decomposition and Factorization API

The Python package I mainly use is TensorLy. _____ Excerpts: [The pyTensorlab provides a broad collection of algorithms for computing the canonical polyadic decomposition (CPD), multilinear singular ...
IEEE

Mitigate the cold start problem in Recommendation System based on Matrix Factorization and Similarity Technique

Abstract: Recommendation System (RS) is a powerful information filtering artificial intelligence tool, which recommend relevant and authentic information for e-commerce user’s onecommerce platform ...
Nature

Fast graph convolutional models incorporating matrix factorization for predicting microbe-disease associations

Revealing the relationship between microbe and disease is of great significance to the diagnosis, treatment, and prevention of disease. To overcome the expensive cost ...