Traditional Gaussian Process Surrogates in the BBOB Framework. - Jakub Repický; Lukás Bajer; Martin Holena (ITAT, 2016)

Ordinal versus metric gaussian process regression in surrogate modelling for CMA evolution strategy. - Zbynek Pitra; Lukás Bajer; Jakub Repický; Martin Holena (GECCO (Companion), 2017)

Overview of surrogate-model versions of covariance matrix adaptation evolution strategy. - Zbynek Pitra; Lukás Bajer; Jakub Repický; Martin Holena (GECCO (Companion), 2017)

Comparison of ordinal and metric gaussian process regression as surrogate models for CMA evolution strategy. - Zbynek Pitra; Lukás Bajer; Jakub Repický; Martin Holena (GECCO (Companion), 2017)

Adaptive Doubly Trained Evolution Control for the Covariance Matrix Adaptation Evolution Strategy. - Zbynek Pitra; Lukás Bajer; Jakub Repický; Martin Holena (ITAT, 2017)

Adaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models. - Jakub Repický; Lukás Bajer; Zbynek Pitra; Martin Holena (ITAT, 2017)

Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy. - Zbynek Pitra; Jakub Repický; Martin Holena (ITAT, 2018)

Automated Selection of Covariance Function for Gaussian process Surrogate Models. - Jakub Repický; Martin Holena; Zbynek Pitra (ITAT, 2018)

Transfer of Knowledge for Surrogate Model Selection in Cost-Aware Optimization. - Zbynek Pitra; Jakub Repický; Martin Holena (IAL@PKDD/ECML, 2018)

Adaptive Selection of Gaussian Process Model for Active Learning in Expensive Optimization. - Jakub Repický; Zbynek Pitra; Martin Holena (IAL@PKDD/ECML, 2018)

Gaussian process surrogate models for the CMA-ES. - Lukás Bajer; Zbynek Pitra; Jakub Repický; Martin Holena (GECCO (Companion), 2019)

Landscape analysis of gaussian process surrogates for the covariance matrix adaptation evolution strategy. - Zbynek Pitra; Jakub Repický; Martin Holena (GECCO, 2019)

Gaussian Process Surrogate Models for the CMA Evolution Strategy. - Lukás Bajer; Zbynek Pitra; Jakub Repický; Martin Holena (Evol. Comput., 2019)