The work introduced a rigorous benchmarking framework that allows for an in-depth comparison of parallel algorithms. It covered two distinct … More
Category: Surrogate Models
Open Access Book “Hyperparameter Tuning for Machine and Deep Learning with R” is finally published
The book “Hyperparameter Tuning for Machine and Deep Learning with R – A Practical Guide” is finally published. The content is … More
Open Access Book “Hyperparameter Tuning for ML and DL with R”: Proof reading started
Today, we received the proofs from Springer. The book will be available soon, see https://link.springer.com/book/9789811951695
Invited Talk @GECCO: Hyperparameter Tuning for Machine and Deep Learning with R
Thomas Bartz-Beielstein will present some ideas from the book “Hyperparameter Tuning for Machine and Deep Learning with R – A … More
SPOT Updates on CRAN
Version: 2.8.2 of the Sequential Parameter Optimization Toolbox is available on CRAN. SPOT is set of tools for model-based optimization … More
Package SPOT_2.5.18.tar.gz has been built for Windows on CRAN
The package SPOT_2.5.18.tar.gz has been built for Windows and is published in the corresponding CRAN directory.R version 4.1.2 (2021-11-01). More: … More
SPOT 2.5.18 uploaded to CRAN. UPDATE: SPOT 2.5.18 is already on CRAN!
That was quick: package sources of SPOT, the Sequential Parameter Optimization Toolbox, Version 2.5.18, are available on CRAN, see https://cran.r-project.org/web/packages/SPOT/index.html. … More
Working Paper: Surrogate Model Based Hyperparameter Tuning for Deep Learning with SPOT
Authors: Thomas Bartz-Beielstein, Frederik Rehbach, Amrita Sen, and Martin ZaeffererCategories: cs.LGMSC-class: 68T07ACM-class: A.1; B.8.0; G.1.6; G.4; I.2.8 A surrogate model … More
Keynote at SAEOpt: Surrogate Model Based Hyperparameter Tuning for Deep Learning with SPOT
Prof. Bartz-Beielstein has been invited as a keynote speaker at the workshop on Surrogate-Assisted Evolutionary Optimisation (SAEOpt) https://saeopt.bitbucket.io/) at GECCO. … More
