15 citations · 21 across the 7 of their papers we have counts for
4 papers · 1 filter
Distributed Matrix Factorization using Asynchrounous Communication
Tom Vander Aa, Imen Chakroun, Tom Haber
Using the matrix factorization technique in machine learning is very common mainly in areas like recommender systems. Despite its high prediction accuracy and its ability to avoid…
Distributed Bayesian Probabilistic Matrix Factorization
Tom Vander Aa, Imen Chakroun, Tom Haber
Matrix factorization is a common machine learning technique for recommender systems. Despite its high prediction accuracy, the Bayesian Probabilistic Matrix Factorization algorithm…
A GPU-accelerated Branch-and-Bound Algorithm for the Flow-Shop Scheduling Problem
Melab Nouredine, Imen Chakroun, Mezmaz Mohand +1
Branch-and-Bound (B&B) algorithms are time intensive tree-based exploration methods for solving to optimality combinatorial optimization problems. In this paper, we investigate the…
An Adaptative Multi-GPU based Branch-and-Bound. A Case Study: the Flow-Shop Scheduling Problem
Imen Chakroun, Nouredine Melab
Solving exactly Combinatorial Optimization Problems (COPs) using a Branch-and-Bound (B&B) algorithm requires a huge amount of computational resources. Therefore, we recently invest…