mlrMBO: A Modular Framework for Model-Based Optimization of Expensive
Black-Box Functions

mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions

9 March 2017

Papers citing "mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions"

17 / 17 papers shown

Title
Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration Julian Rodemann Federico Croppi Philipp Arens Yusuf Sale J. Herbinger B. Bischl Eyke Hüllermeier Thomas Augustin Conor J. Walsh Giuseppe Casalicchio 46 7 0 07 Mar 2024
Mastering the exploration-exploitation trade-off in Bayesian Optimization Antonio Candelieri 34 1 0 15 May 2023
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization Matthieu Dorier Romain Egele Prasanna Balaprakash Jaehoon Koo Sandeep Madireddy Srinivasan Ramesh A. Malony R. Ross 21 10 0 03 Oct 2022
Explaining Hyperparameter Optimization via Partial Dependence Plots Julia Moosbauer J. Herbinger Giuseppe Casalicchio Marius Lindauer Bernd Bischl 47 56 0 08 Nov 2021
A comparison of mixed-variables Bayesian optimization approaches Jhouben Cuesta Ramirez Rodolphe Le Riche O. Roustant G. Perrin Cédric Durantin A. Glière 19 17 0 30 Oct 2021
A portfolio approach to massively parallel Bayesian optimization M. Binois Nicholson T. Collier J. Ozik 27 9 0 18 Oct 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges B. Bischl Martin Binder Michel Lang Tobias Pielok Jakob Richter ... Theresa Ullmann Marc Becker A. Boulesteix Difan Deng Marius Lindauer 85 448 0 13 Jul 2021
Understanding the effect of hyperparameter optimization on machine learning models for structure design problems Xianping Du Hongyi Xu Feng Zhu AI4CE 9 44 0 04 Jul 2020
Sherpa: Robust Hyperparameter Optimization for Machine Learning L. Hertel Julian Collado Peter Sadowski J. Ott Pierre Baldi 86 103 0 08 May 2020
Initial Design Strategies and their Effects on Sequential Model-Based Optimization Jakob Bossek Carola Doerr P. Kerschke 18 26 0 30 Mar 2020
Expected Improvement versus Predicted Value in Surrogate-Based Optimization Frederik Rehbach Martin Zaefferer B. Naujoks T. Bartz-Beielstein 15 24 0 09 Jan 2020
Empowering individual trait prediction using interactions D. Gola I. König 35 5 0 25 Jan 2019
OBOE: Collaborative Filtering for AutoML Model Selection Chengrun Yang Yuji Akimoto Dae Won Kim Madeleine Udell 15 100 0 09 Aug 2018
Automatic Gradient Boosting Janek Thomas Stefan Coors B. Bischl 21 23 0 10 Jul 2018
Hyperparameters and Tuning Strategies for Random Forest Philipp Probst Marvin N. Wright A. Boulesteix 33 1,351 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 23 319 0 29 Mar 2018
OpenML: An R Package to Connect to the Machine Learning Platform OpenML Giuseppe Casalicchio Jakob Bossek Michel Lang Dominik Kirchhoff P. Kerschke B. Hofner H. Seibold Joaquin Vanschoren B. Bischl VLM LRM 15 53 0 05 Jan 2017