Google Discover is largely a mystery to publishers and the search marketing community even though Google has published ...

This repository explores how well a Biased Latent Matrix Factorization (BLMF) recommender system performs when trained on extremely sparse rating matrices, using a reduced sample of the MovieLens 32M ...

Digital Matrix Systems, Inc. (DMS) today announced the addition of ten new tri-bureau attributes to its DMS Summary Attributes® library. These enhancements address emerging trends in consumer credit ...

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...

ABSTRACT: In this paper, an Optimal Predictive Modeling of Nonlinear Transformations “OPMNT” method has been developed while using Orthogonal Nonnegative Matrix Factorization “ONMF” with the ...

There once was a time where going viral on the internet actually meant something. Long ago, in the early 2010s, 500,000 views could actually land you on daytime TV, where you could experience the ...

Yandex has introduced ARGUS (AutoRegressive Generative User Sequential modeling), a large-scale transformer-based framework for recommender systems that scales up to one billion parameters. This ...

PLANO, Texas--(BUSINESS WIRE)--Digital Matrix Systems, Inc. (DMS) announced today that Mariner Finance, LLC (“Mariner Finance”) has selected the company’s CreditBrowser® solution. Baltimore-based ...

Abstract: Recommender systems have gained significant attention for their ability to model user preferences and predict future trends. Collaborative filtering, particularly through Non-negative Matrix ...

While Nvidia’s GB200 significantly outperforms Huawei CloudMatrix 384 at the chip level, Huawei gains an advantage at the system level by integrating five to six times more compute and HBM chips.