Two Gaussian Approaches to Black-Box Optomization
Neural and Evolutionary Computing
2014-12-01 v1 Artificial Intelligence
Abstract
Outline of several strategies for using Gaussian processes as surrogate models for the covariance matrix adaptation evolution strategy (CMA-ES).
Cite
@article{arxiv.1411.7806,
title = {Two Gaussian Approaches to Black-Box Optomization},
author = {Lukáš Bajer and Martin Holeňa},
journal= {arXiv preprint arXiv:1411.7806},
year = {2014}
}
Comments
9 pages
Related papers
View all related →
Neural and Evolutionary Computing · Computer Science
Adaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models
Jakub Repicky, Lukas Bajer, Zbynek Pitra, Martin Holena
2017-10-02
Neural and Evolutionary Computing · Computer Science
CMA-ES with Radial Basis Function Surrogate for Black-Box Optimization
Farshid Farhadi Khouzani, Abdolreza Mirzaei, Paul La Plante, Laxmi Gewali
2025-05-23
Neural and Evolutionary Computing · Computer Science
CMA-ES with Adaptive Reevaluation for Multiplicative Noise
Kento Uchida, Kenta Nishihara, Shinichi Shirakawa
2024-05-21
Machine Learning · Computer Science
The Hessian Estimation Evolution Strategy
Tobias Glasmachers, Oswin Krause
2020-06-11
Neural and Evolutionary Computing · Computer Science
Evolving the Structure of Evolution Strategies
Sander van Rijn, Hao Wang, Matthijs van Leeuwen, Thomas Bäck
2018-08-20
Neural and Evolutionary Computing · Computer Science
Covariance Matrix Adaptation Evolution Strategy Assisted by Principal Component Analysis
Yangjie Mei, Hao Wang
2021-05-12
Neural and Evolutionary Computing · Computer Science
MMES: Mixture Model based Evolution Strategy for Large-Scale Optimization
Xiaoyu He, Zibin Zheng, Yuren Zhou
2022-03-25
Neural and Evolutionary Computing · Computer Science
A parallel implementation of the covariance matrix adaptation evolution strategy
Najeeb Khan
2018-05-30
Machine Learning · Statistics
Bayesian Optimization using Deep Gaussian Processes
Ali Hebbal, Loic Brevault, Mathieu Balesdent, El-Ghazali Talbi +1
2019-05-10
Machine Learning · Computer Science
Empirical Evaluation of Contextual Policy Search with a Comparison-based Surrogate Model and Active Covariance Matrix Adaptation
Alexander Fabisch
2019-04-16
Neural and Evolutionary Computing · Computer Science
Limited-Memory Matrix Adaptation for Large Scale Black-box Optimization
Ilya Loshchilov, Tobias Glasmachers, Hans-Georg Beyer
2017-05-19
Neural and Evolutionary Computing · Computer Science
An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise
Catalin-Viorel Dinu, Yash J. Patel, Xavier Bonet-Monroig, Hao Wang
2025-06-04
Machine Learning · Computer Science
Hyper-optimization with Gaussian Process and Differential Evolution Algorithm
Jakub Klus, Pavel Grunt, Martin Dobrovolný
2021-01-27
Machine Learning · Computer Science
The CMA Evolution Strategy: A Tutorial
Nikolaus Hansen
2023-03-13
Systems and Control · Computer Science
Using CMA-ES for tuning coupled PID controllers within models of combustion engines
Katerina Henclova
2017-06-07
Neural and Evolutionary Computing · Computer Science
A Covariance Matrix Self-Adaptation Evolution Strategy for Optimization under Linear Constraints
Patrick Spettel, Hans-Georg Beyer, Michael Hellwig
2018-09-24
Neural and Evolutionary Computing · Computer Science
A Simple Yet Efficient Rank One Update for Covariance Matrix Adaptation
Zhenhua Li, Qingfu Zhang
2017-10-24
Machine Learning · Statistics
Variational Calibration of Computer Models
Sébastien Marmin, Maurizio Filippone
2018-10-30
Neural and Evolutionary Computing · Computer Science
CMA-ES for Hyperparameter Optimization of Deep Neural Networks
Ilya Loshchilov, Frank Hutter
2016-04-26
Systems and Control · Electrical Eng. & Systems
Memetic Covariance Matrix Adaptation Evolution Strategy for Bilinear Matrix Inequality Problems in Control System Design
Syue-Cian Lin, Wei-Yu Chiu, Chien-Feng Wu
2026-01-14
Neural and Evolutionary Computing · Computer Science
Distributed Evolution Strategies with Multi-Level Learning for Large-Scale Black-Box Optimization
Qiqi Duan, Chang Shao, Guochen Zhou, Minghan Zhang +2
2024-10-14
Neural and Evolutionary Computing · Computer Science
CMA-ES with Two-Point Step-Size Adaptation
Nikolaus Hansen
2008-12-18
Distributed, Parallel, and Cluster Computing · Computer Science
Massively parallel CMA-ES with increasing population
David Redon, Pierre Fortin, Bilel Derbel, Miwako Tsuji +1
2024-10-02
Neural and Evolutionary Computing · Computer Science
CMA-ES with Learning Rate Adaptation
Masahiro Nomura, Youhei Akimoto, Isao Ono
2024-09-30
Neural and Evolutionary Computing · Computer Science
(1+1)-CMA-ES with Margin for Discrete and Mixed-Integer Problems
Yohei Watanabe, Kento Uchida, Ryoki Hamano, Shota Saito +2
2023-05-02