24 citations · 88 across the 12 of their papers we have counts for
4 papers · 1 filter
A Data-driven Approach to Neural Architecture Search Initialization
Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu
Algorithmic design in neural architecture search (NAS) has received a lot of attention, aiming to improve performance and reduce computational cost. Despite the great advances made…
Fitness Landscape Footprint: A Framework to Compare Neural Architecture Search Problems
Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu
Neural architecture search is a promising area of research dedicated to automating the design of neural network models. This field is rapidly growing, with a surge of methodologies…
Lessons from the Clustering Analysis of a Search Space: A Centroid-based Approach to Initializing NAS
Kalifou Rene Traore, Andrés Camero, Xiao Xiang Zhu
Lots of effort in neural architecture search (NAS) research has been dedicated to algorithmic development, aiming at designing more efficient and less costly methods. Nonetheless,…
Reliable and Fast Recurrent Neural Network Architecture Optimization
Andrés Camero, Jamal Toutouh, Enrique Alba
This article introduces Random Error Sampling-based Neuroevolution (RESN), a novel automatic method to optimize recurrent neural network architectures. RESN combines an evolutionar…