A Practical Guide with Examples in Python A new book on the important topic of Online Machine Learning has now been … More
Category: Artificial Intellligence
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
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
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
AI-based approach to detect, classify and localize underwater events. Preprint “Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs” available on arXiv
The preprint of the paper “Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs” is available on … 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