51 citations · 65 across the 3 of their papers we have counts for
4 papers
Multi-fidelity modeling with different input domain definitions using Deep Gaussian Processes
Ali Hebbal, Loic Brevault, Mathieu Balesdent +2
Multi-fidelity approaches combine different models built on a scarce but accurate data-set (high-fidelity data-set), and a large but approximate one (low-fidelity data-set) in orde…
Bayesian Optimization using Deep Gaussian Processes
Ali Hebbal, Loic Brevault, Mathieu Balesdent +2
Bayesian Optimization using Gaussian Processes is a popular approach to deal with the optimization of expensive black-box functions. However, because of the a priori on the station…
Efficient Global Optimization using Deep Gaussian Processes
Ali Hebbal, Loic Brevault, Mathieu Balesdent +2
Efficient Global Optimization (EGO) is widely used for the optimization of computationally expensive black-box functions. It uses a surrogate modeling technique based on Gaussian P…
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…