HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO

14 September 2021

Katharina Eggensperger

Papers citing "HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO"

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Title
FigBO: A Generalized Acquisition Function Framework with Look-Ahead Capability for Bayesian Optimization Hui Chen Xuhui Fan Zhangkai Wu Longbing Cao LLMAG 33 0 0 28 Apr 2025
A Balanced Approach of Rapid Genetic Exploration and Surrogate Exploitation for Hyperparameter Optimization Chul Kim Inwhee Joe 16 2 0 10 Apr 2025
Offline Model-Based Optimization: Comprehensive Review Minsu Kim Jiayao Gu Ye Yuan Taeyoung Yun Z. Liu Yoshua Bengio Can Chen OffRL 51 2 0 21 Mar 2025
Hyperparameter Importance Analysis for Multi-Objective AutoML Daphne Theodorakopoulos Frederic Stahl Marius Lindauer 54 2 0 03 Jan 2025
Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey Yang Gu Hengyu You Jian Cao Muran Yu Haoran Fan Shiyou Qian LM&MA AI4CE 33 3 0 11 Nov 2024
Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization Zeyuan Ma Hongshu Guo Yue-jiao Gong Jun Zhang Kay Chen Tan 92 2 0 01 Nov 2024
Efficient Deep Learning Board: Training Feedback Is Not All You Need Lina Gong Qi Gao Peng Li Mingqiang Wei Fei Wu OOD 16 0 0 17 Oct 2024
A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes Jake Robertson Thorsten Schmidt Frank Hutter Noor H. Awad 20 0 0 17 Oct 2024
LMEMs for post-hoc analysis of HPO Benchmarking Anton Geburek Neeratyoy Mallik Danny Stoll Xavier Bouthillier Frank Hutter 11 0 0 05 Aug 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization Jacob O. Tørring Carl Hvarfner Luigi Nardi Magnus Sjalander 31 0 0 24 Jun 2024
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization Thomas Nagler Lennart Schneider B. Bischl Matthias Feurer 30 2 0 24 May 2024
Trajectory-Based Multi-Objective Hyperparameter Optimization for Model Retraining Wenyu Wang Zheyi Fan S. Ng 11 0 0 24 May 2024
Position: Leverage Foundational Models for Black-Box Optimization Xingyou Song Yingtao Tian Robert Tjarko Lange Chansoo Lee Yujin Tang Yutian Chen 25 3 0 06 May 2024
Position: Why We Must Rethink Empirical Research in Machine Learning Moritz Herrmann F. J. D. Lange Katharina Eggensperger Giuseppe Casalicchio Marcel Wever Matthias Feurer David Rügamer Eyke Hüllermeier A. Boulesteix Bernd Bischl 28 0 0 03 May 2024
The Unreasonable Effectiveness Of Early Discarding After One Epoch In Neural Network Hyperparameter Optimization Romain Egele Felix Mohr Tom Viering Prasanna Balaprakash 21 5 0 05 Apr 2024
Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks Shuhei Watanabe Neeratyoy Mallik Eddie Bergman Frank Hutter 12 0 0 04 Mar 2024
Multi-Fidelity Methods for Optimization: A Survey Ke Li Fan Li AI4CE 17 6 0 15 Feb 2024
Strong convexity-guided hyper-parameter optimization for flatter losses Rahul Yedida Snehanshu Saha 8 0 0 07 Feb 2024
Large Language Models to Enhance Bayesian Optimization Tennison Liu Nicolás Astorga Nabeel Seedat M. Schaar 50 44 0 06 Feb 2024
Poisson Process for Bayesian Optimization Xiaoxing Wang Jiaxing Li Chao Xue Wei Liu Weifeng Liu Xiaokang Yang Junchi Yan Dacheng Tao 20 1 0 05 Feb 2024
Large Language Model Agent for Hyper-Parameter Optimization Siyi Liu Chen Gao Yong Li 23 18 0 02 Feb 2024
Long-run Behaviour of Multi-fidelity Bayesian Optimisation G. Dovonon Jakob Zeitler 11 1 0 19 Dec 2023
Using Large Language Models for Hyperparameter Optimization Michael Ruogu Zhang Nishkrit Desai Juhan Bae Jonathan Lorraine Jimmy Ba 21 49 0 07 Dec 2023
Scalable Meta-Learning with Gaussian Processes Petru Tighineanu Lukas Großberger P. Baireuther Kathrin Skubch Stefan Falkner Julia Vinogradska Felix Berkenkamp 12 4 0 01 Dec 2023
A systematic study comparing hyperparameter optimization engines on tabular data Balazs Kegl 6 0 0 27 Nov 2023
On the Hyperparameter Loss Landscapes of Machine Learning Models: An Exploratory Study Mingyu Huang Ke Li 10 3 0 23 Nov 2023
TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications David Salinas Nick Erickson 14 5 0 06 Nov 2023
Machine learning's own Industrial Revolution Yuan Luo Song Han Jingjing Liu AI4CE 8 0 0 04 Nov 2023
Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations Jungtaek Kim Mingxuan Li Oliver Hinder Paul W. Leu 11 1 0 29 Oct 2023
Deterministic Langevin Unconstrained Optimization with Normalizing Flows James M. Sullivan U. Seljak 19 0 0 01 Oct 2023
Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives Romain Egele Tyler Chang Yixuan Sun V. Vishwanath Prasanna Balaprakash 23 2 0 26 Sep 2023
HomOpt: A Homotopy-Based Hyperparameter Optimization Method Sophia J. Abraham K. D. G. Maduranga Jeffery Kinnison Zachariah Carmichael Jonathan D. Hauenstein Walter J. Scheirer 13 0 0 07 Aug 2023
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization? Romain Egele Isabelle M Guyon Yixuan Sun Prasanna Balaprakash 14 2 0 28 Jul 2023
SigOpt Mulch: An Intelligent System for AutoML of Gradient Boosted Trees Aleksei G. Sorokin Xinran Zhu E. Lee Bolong Cheng 15 2 0 10 Jul 2023
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization Jia-Yu Pan Stefan Falkner Felix Berkenkamp Joaquin Vanschoren 11 1 0 07 Jul 2023
Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization Kamil Dreczkowski Antoine Grosnit Haitham Bou-Ammar 11 4 0 16 Jun 2023
Multi-Fidelity Multi-Armed Bandits Revisited Xuchuang Wang Qingyun Wu Wei-Neng Chen John C. S. Lui 18 2 0 13 Jun 2023
Provably Efficient Bayesian Optimization with Unknown Gaussian Process Hyperparameter Estimation Huong Ha Vu-Linh Nguyen Hung Tran-The Hongyu Zhang Xiuzhen Zhang A. Hengel 22 1 0 12 Jun 2023
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization C. Benjamins E. Raponi Anja Jankovic Carola Doerr Marius Lindauer TPM 6 3 0 07 Jun 2023
Hyperparameters in Reinforcement Learning and How To Tune Them Theresa Eimer Marius Lindauer Roberta Raileanu OffRL 14 33 0 02 Jun 2023
Python Wrapper for Simulating Multi-Fidelity Optimization on HPO Benchmarks without Any Wait Shuhei Watanabe 20 1 0 27 May 2023
PFNs4BO: In-Context Learning for Bayesian Optimization Samuel G. Müller Matthias Feurer Noah Hollmann Frank Hutter 15 33 0 27 May 2023
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes A. Maraval Matthieu Zimmer Antoine Grosnit H. Ammar BDL 14 15 0 25 May 2023
MO-DEHB: Evolutionary-based Hyperband for Multi-Objective Optimization Noor H. Awad Ayush Sharma Philipp Muller Janek Thomas Frank Hutter 15 1 0 08 May 2023
Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance Shuhei Watanabe 6 114 0 21 Apr 2023
Towards a Benchmarking Suite for Kernel Tuners Jacob O. Tørring Ben van Werkhoven Filip Petrovic Floris-Jan Willemsen Jiri Filipovic A. Elster 9 3 0 15 Mar 2023
A Coreset Learning Reality Check Fred Lu Edward Raff James Holt 12 5 0 15 Jan 2023
HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes Z. Fan Xinran Han Z. Wang 11 3 0 20 Dec 2022
Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator Shuhei Watanabe Noor H. Awad Masaki Onishi Frank Hutter 21 6 0 13 Dec 2022
Neighbor Regularized Bayesian Optimization for Hyperparameter Optimization Lei Cui Yangguang Li Xin Lu Dong An Fenggang Liu BDL 10 0 0 07 Oct 2022