Version 0.0.1 published on GitHub The notebooks in the GitHub repository https://github.com/sn-code-inside/online-machine-learning are part of the supplementary material of the … More
Category: Machine Learning
New Book: Online Machine Learning
A Practical Guide with Examples in Python A new book on the important topic of Online Machine Learning has now been … More
MESS 2024: Metaheuristics Summer School
Automated Deep Learning meets High-Performance Computing The 3rd international Metaheuristics Summer School – MESS 2024 – (https://www.ants-lab.it/mess2024/) is aimed at qualified … More
spotRiver v0.2.10 released
Starting with River 0.21.0, River’s learn_one and learn_many methods of each estimator don’t not return anything anymore, see https://riverml.xyz/0.21.0/releases/0.21.0/. This … More
More than 10 000 Accesses: “Hyperparameter Tuning for Machine and Deep Learning” Book
This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice … More
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
SPOTMisc 1.19.26 is on its Way to CRAN
SPOTMisc: Misc Extensions for the ‘SPOT’ Package Implements additional models, simulation tools, and interfaces as extensions to ‘SPOT’. It provides … More
CfP: Special Session on Evolutionary Transfer Learning and Transfer Optimisation
2022 IEEE World Congress on Computational Intelligence (WCCI)/ IEEE Congress on Evolutionary Computation (CEC) 18 – 23 July 2022, Padova, … More
Hyperparameter Tuning Survey Paper: Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization
The working paper “Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization” by Eva Bartz, Martin Zaefferer, Olaf Mersmann, Thomas Bartz-Beielstein was published on … 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