Explaining Hyperparameter Optimization via Partial Dependence Plots

8 November 2021

Papers citing "Explaining Hyperparameter Optimization via Partial Dependence Plots"

8 / 8 papers shown

Title
Hyperparameter Importance Analysis for Multi-Objective AutoML Daphne Theodorakopoulos Frederic Stahl Marius Lindauer 101 3 0 03 Jan 2025
Efficient and Accurate Explanation Estimation with Distribution Compression Hubert Baniecki Giuseppe Casalicchio Bernd Bischl Przemyslaw Biecek FAtt 93 4 0 26 Jun 2024
Explainable Bayesian Optimization Tanmay Chakraborty Christin Seifert Christian Wirth 112 5 0 24 Jan 2024
Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL Lucas Zimmer Marius Lindauer Frank Hutter MU 113 92 0 24 Jun 2020
A Simple and Effective Model-Based Variable Importance Measure Brandon M. Greenwell Bradley C. Boehmke Andrew J. McCarthy FAtt TDI 36 229 0 12 May 2018
Tunability: Importance of Hyperparameters of Machine Learning Algorithms Philipp Probst B. Bischl A. Boulesteix 60 614 0 26 Feb 2018
Algorithm Runtime Prediction: Methods & Evaluation Frank Hutter Lin Xu Holger H. Hoos Kevin Leyton-Brown 71 419 0 05 Nov 2012
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 353 7,936 0 13 Jun 2012