Experimental Investigation and Evaluation of Model-based Hyperparameter
Optimization

Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization

19 July 2021

Martin Zaefferer

Thomas Bartz-Beielstein

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Papers citing "Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization"

19 / 19 papers shown

Title
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice Li Yang Abdallah Shami AI4CE 176 2,108 0 30 Jul 2020
Expected Improvement versus Predicted Value in Surrogate-Based Optimization Frederik Rehbach Martin Zaefferer B. Naujoks Thomas Bartz-Beielstein 107 25 0 09 Jan 2020
Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation George De Ath Richard Everson Alma A. M. Rahat J. Fieldsend 73 100 0 28 Nov 2019
An Experimental Comparison of Old and New Decision Tree Algorithms Arman Zharmagambetov Suryabhan Singh Hada Miguel Á. Carreira-Perpiñán Magzhan Gabidolla 367 16 0 08 Nov 2019
A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization Yan Wang X. Ni 26 97 0 24 Jan 2019
How Complex is your classification problem? A survey on measuring classification complexity A. C. Lorena L. P. F. Garcia Jens Lehmann M. D. Souto T. Ho 46 233 0 10 Aug 2018
Gradient and Newton Boosting for Classification and Regression Fabio Sigrist 30 62 0 09 Aug 2018
Automatic Gradient Boosting Janek Thomas Stefan Coors B. Bischl 83 23 0 10 Jul 2018
Hyperparameters and Tuning Strategies for Random Forest Philipp Probst Marvin N. Wright A. Boulesteix 130 1,400 0 10 Apr 2018
Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data P. Schratz Jannes Muenchow E. Iturritxa Jakob Richter A. Brenning 77 328 0 29 Mar 2018
Tunability: Importance of Hyperparameters of Machine Learning Algorithms Philipp Probst B. Bischl A. Boulesteix 60 619 0 26 Feb 2018
Visualizing the Loss Landscape of Neural Nets Hao Li Zheng Xu Gavin Taylor Christoph Studer Tom Goldstein 258 1,896 0 28 Dec 2017
Hyperparameter Importance Across Datasets J. N. van Rijn Frank Hutter 48 240 0 12 Oct 2017
To tune or not to tune the number of trees in random forest? Philipp Probst A. Boulesteix 64 391 0 16 May 2017
The True Destination of EGO is Multi-local Optimization Simon Wessing Mike Preuss 25 13 0 19 Apr 2017
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R Marvin N. Wright A. Ziegler 272 2,787 0 18 Aug 2015
OpenML: networked science in machine learning Joaquin Vanschoren Jan N. van Rijn B. Bischl Luís Torgo FedML AI4CE 163 1,327 0 29 Jul 2014
Understanding Random Forests: From Theory to Practice Gilles Louppe 101 745 0 28 Jul 2014
ParamILS: An Automatic Algorithm Configuration Framework Frank Hutter Thomas Stuetzle Kevin Leyton-Brown T. Stützle 90 1,067 0 15 Jan 2014

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