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Category: Machine Learning

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

Hyperparameter Tuning for Machine and Deep Learning with R

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

Cognitive Capabilities for the Cognitive Architecture for Artificial Intelligence (CAAI) in Cyber-Physical Production Systems (Open Access Article)

Our (Jan Strohschein, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke, Natalia Moriz & Thomas Bartz-Beielstein) article “Cognitive capabilities for the CAAI in cyber-physical production systems” has been … More

Machine Learning Collage by Robert Lange: Four Deep Learning Papers to Read in June 2021

Robert Lange drafts one-slide visual summaries (“ML collages) of his favorite recent papers (published on towardsdatascience), e.g., Also interesting: “What … More

What is Uncertainty in Machine Learning? Presentation from Matias Valdenegro (German Research Center for Artificial Intelligence)

Dr. Matias Valdenegro Toro from the German Research Center for Artificial Intelligence, Bremen talked about “Uncertainty Quantification in Computer Vision … More

RStudio: Deep Learning with Keras Cheatsheet

Keras is a high-level neural networks API developed with a focus on enabling fast experimentation. Keras supports both convolution based networks and … More

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Recent Posts

  • More than 10 000 Accesses: “Hyperparameter Tuning for Machine and Deep Learning” Book
  • CfP: GECCO 2023
  • Another Successful PhD Defense: Frederik Rehbach on “Enhancing Surrogate-Based-Optimization Through Parallelization“
  •  CfP: Applied Soft Computing Special Issue on Neuroevolution Techniques: Methods and Applications
  • Open Access Book “Hyperparameter Tuning for Machine and Deep Learning with R” is finally published

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