15 citations · 21 across the 7 of their papers we have counts for
3 papers · 1 filter
Guidelines for enhancing data locality in selected machine learning algorithms
Imen Chakroun, Tom Vander Aa, Thomas J. Ashby
To deal with the complexity of the new bigger and more complex generation of data, machine learning (ML) techniques are probably the first and foremost used. For ML algorithms to p…
Reviewing Data Access Patterns and Computational Redundancy for Machine Learning Algorithms
Imen Chakroun, Tom Vander Aa, Tom Ashby
Machine learning (ML) is probably the first and foremost used technique to deal with the size and complexity of the new generation of data. In this paper, we analyze one of the mea…
SMURFF: a High-Performance Framework for Matrix Factorization
Tom Vander Aa, Imen Chakroun, Thomas J. Ashby +10
Bayesian Matrix Factorization (BMF) is a powerful technique for recommender systems because it produces good results and is relatively robust against overfitting. Yet BMF is more c…