Guidelines for enhancing data locality in selected machine learning algorithms

no code implementations • 9 Jan 2020 • Imen Chakroun, Tom Vander Aa, Thomas J. Ashby

In this paper, we analyze one of the means to increase the performances of machine learning algorithms which is exploiting data locality.

BIG-bench Machine Learning

SMURFF: a High-Performance Framework for Matrix Factorization

no code implementations • 4 Apr 2019 • Tom Vander Aa, Imen Chakroun, Thomas J. Ashby, Jaak Simm, Adam Arany, Yves Moreau, Thanh Le Van, José Felipe Golib Dzib, Jörg Wegner, Vladimir Chupakhin, Hugo Ceulemans, Roel Wuyts, Wilfried Verachtert

Bayesian Matrix Factorization (BMF) is a powerful technique for recommender systems because it produces good results and is relatively robust against overfitting.

Activity Prediction Recommendation Systems +1