SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

20 September 2021

Marius Lindauer

Katharina Eggensperger

Papers citing "SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization"

24 / 24 papers shown

Title
UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model T. Kaiser Thomas Norrenbrock Bodo Rosenhahn 34 0 0 08 May 2025
Automated Machine Learning for Remaining Useful Life Predictions Marc Zoller Fabian Mauthe P. Zeiler Marius Lindauer Marco F. Huber AI4CE 49 5 0 20 Jan 2025
Distributed Thompson sampling under constrained communication Saba Zerefa Zhaolin Ren Haitong Ma Na Li 25 1 0 03 Jan 2025
Hyperparameter Importance Analysis for Multi-Objective AutoML Daphne Theodorakopoulos Frederic Stahl Marius Lindauer 57 2 0 03 Jan 2025
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
Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection Matteo Zecchin Sangwoo Park Osvaldo Simeone LM&MA 45 3 0 24 Sep 2024
Uncertainty and Prediction Quality Estimation for Semantic Segmentation via Graph Neural Networks Edgar Heinert Stephan Tilgner Timo Palm Matthias Rottmann UQCV 19 0 0 17 Sep 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization Jacob O. Tørring Carl Hvarfner Luigi Nardi Magnus Sjalander 33 0 0 24 Jun 2024
Accel-NASBench: Sustainable Benchmarking for Accelerator-Aware NAS Afzal Ahmad Linfeng Du Zhiyao Xie Wei Zhang 18 0 0 09 Apr 2024
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models Lennart Schneider B. Bischl Janek Thomas 15 6 0 17 Jul 2023
A Context-Aware Cutting Plane Selection Algorithm for Mixed-Integer Programming Mark Turner Timo Berthold Mathieu Besançon 13 1 0 14 Jul 2023
LEO: Learning Efficient Orderings for Multiobjective Binary Decision Diagrams R. Patel Elias Boutros Khalil 10 0 0 06 Jul 2023
Automatic MILP Solver Configuration By Learning Problem Similarities Abdelrahman I. Hosny Sherief Reda 16 4 0 02 Jul 2023
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization Hyeon-Seob Kim Minsu Kim Sungsoo Ahn Jinkyoo Park OffRL 21 7 0 02 Jun 2023
Dynamic Grasping with a Learned Meta-Controller Yinsen Jia Jingxi Xu Dinesh Jayaraman Shuran Song 31 4 0 16 Feb 2023
PI is back! Switching Acquisition Functions in Bayesian Optimization C. Benjamins E. Raponi Anja Jankovic K. Blom Maria Laura Santoni Marius Lindauer Carola Doerr 8 4 0 02 Nov 2022
Efficiently Controlling Multiple Risks with Pareto Testing Bracha Laufer-Goldshtein Adam Fisch Regina Barzilay Tommi Jaakkola 25 16 0 14 Oct 2022
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces Alexander Thebelt Calvin Tsay Robert M. Lee Nathan Sudermann-Merx David Walz B. Shafei Ruth Misener UQCV BDL 17 10 0 02 Jul 2022
Automated Dynamic Algorithm Configuration Steven Adriaensen André Biedenkapp Gresa Shala Noor H. Awad Theresa Eimer Marius Lindauer Frank Hutter 21 36 0 27 May 2022
Efficient Automated Deep Learning for Time Series Forecasting Difan Deng Florian Karl Frank Hutter Bernd Bischl Marius Lindauer AI4TS 19 16 0 11 May 2022
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO Katharina Eggensperger Philip Muller Neeratyoy Mallik Matthias Feurer René Sass Aaron Klein Noor H. Awad Marius Lindauer Frank Hutter 24 98 0 14 Sep 2021
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning Matthias Feurer Katharina Eggensperger Stefan Falkner Marius Lindauer Frank Hutter 19 260 0 08 Jul 2020
Time Efficiency in Optimization with a Bayesian-Evolutionary Algorithm Gongjin Lan Jakub M. Tomczak D. Roijers A. E. Eiben 67 66 0 04 May 2020
NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search Arber Zela Julien N. Siems Frank Hutter 66 146 0 28 Jan 2020