Google quietly published a research paper on personalized semantics for recommender systems like Google Discover and YouTube.

Microsoft-backed (NASDAQ: MSFT) semiconductor company d-Matrix on Nov. 12 announced it raised $275 million while claiming its artificial intelligence chips outperform graphics processing units-based ...

Abstract: As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest neighbor techniques for producing product recommendations, allowing the ...

probabilistic matrix factorization for recommender system based on gibbs sampling and variational mean field - final projects of probablistic graphical models course ...

probabilistic matrix factorization for recommender system based on gibbs sampling and variational mean field - final projects of probablistic graphical models course Used Probabilistic Matrix ...

Like in many other research areas, deep learning (DL) is increasingly adopted in music recommendation systems (MRS). Deep neural networks are used in this domain particularly for extracting latent ...

Abstract: In the area of computational intelligence, recommender systems play important roles in both commercial and social activities. Among its implement methods, matrix factorization is one of the ...

A prominent approach in collaborative filtering based recommender systems is using dimensionality reduction (matrix factorization) techniques to map users and items into low-dimensional vectors. In ...