pySOT and POAP: An event-driven asynchronous framework for surrogate optimization

30 July 2019

Papers citing "pySOT and POAP: An event-driven asynchronous framework for surrogate optimization"

5 / 5 papers shown

Title
Genetically programmable optical random neural networks Bora Çarpinlioglu Bahrem Serhat Danis 41 5 0 19 Mar 2024
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 Ryan Turner David Eriksson M. McCourt J. Kiili Eero Laaksonen Zhen Xu Isabelle M Guyon BDL 30 289 0 20 Apr 2021
libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations S. Hudson Jeffrey Larson John-Luke Navarro Stefan M. Wild 16 28 0 16 Apr 2021
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation Alexander I. Cowen-Rivers Wenlong Lyu Rasul Tutunov Zhi Wang Antoine Grosnit ... A. Maraval Hao Jianye Jun Wang Jan Peters H. Ammar 27 74 0 07 Dec 2020
On the implementation of a global optimization method for mixed-variable problems G. Nannicini 16 19 0 04 Sep 2020