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BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis
  of Hyperparameters

BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters

16 August 2019
Marius Lindauer
Katharina Eggensperger
Matthias Feurer
André Biedenkapp
Joshua Marben
Philip Muller
Katharina Eggensperger
ArXiv (abs)PDFHTML

Papers citing "BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters"

28 / 28 papers shown
Explainable Swarm: A Methodological Framework for Interpreting Swarm Intelligence
Explainable Swarm: A Methodological Framework for Interpreting Swarm IntelligenceInternational Conference on Process Control (ICPC), 2025
Nitin Gupta
Bapi Dutta
Anupam Yadav
220
0
0
08 Sep 2025
Modeling Hierarchical Spaces: A Review and Unified Framework for Surrogate-Based Architecture Design
Modeling Hierarchical Spaces: A Review and Unified Framework for Surrogate-Based Architecture Design
P. Saves
Edward Hallé-Hannan
J. Bussemaker
Y. Diouane
N. Bartoli
AI4CE
217
0
0
27 Jun 2025
carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks
carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks
C. Benjamins
Helena Graf
Sarah Segel
Difan Deng
Tim Ruhkopf
...
Katharina Eggensperger
Katharina Eggensperger
Frank Hutter
Carola Doerr
Marius Lindauer
280
3
0
06 Jun 2025
Enhancing Explainability and Reliable Decision-Making in Particle Swarm Optimization through Communication Topologies
Enhancing Explainability and Reliable Decision-Making in Particle Swarm Optimization through Communication Topologies
Nitin Gupta
Indu Bala
Bapi Dutta
Luis Martínez
Anupam Yadav
82
2
0
17 Apr 2025
In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design
  of Heuristics
In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of HeuristicsACM Transactions on Evolutionary Learning and Optimization (ACM TELO), 2024
Niki van Stein
Diederick Vermetten
Thomas Bäck
227
33
0
07 Oct 2024
An Autotuning-based Optimization Framework for Mixed-kernel SVM
  Classifications in Smart Pixel Datasets and Heterojunction Transistors
An Autotuning-based Optimization Framework for Mixed-kernel SVM Classifications in Smart Pixel Datasets and Heterojunction Transistors
Xingfu Wu
Tupendra Oli
ustin H. Qian
V. Taylor
M. Hersam
V. Sangwan
214
3
0
26 Jun 2024
Accel-NASBench: Sustainable Benchmarking for Accelerator-Aware NAS
Accel-NASBench: Sustainable Benchmarking for Accelerator-Aware NAS
Afzal Ahmad
Linfeng Du
Zhiyao Xie
Wei Zhang
395
0
0
09 Apr 2024
Efficient Automatic Tuning for Data-driven Model Predictive Control via
  Meta-Learning
Efficient Automatic Tuning for Data-driven Model Predictive Control via Meta-Learning
Baoyu Li
William Edwards
Kris Hauser
161
0
0
30 Mar 2024
Explainable Benchmarking for Iterative Optimization Heuristics
Explainable Benchmarking for Iterative Optimization Heuristics
Niki van Stein
Diederick Vermetten
Anna V. Kononova
Thomas Bäck
401
24
0
31 Jan 2024
X Hacking: The Threat of Misguided AutoML
X Hacking: The Threat of Misguided AutoML
Rahul Sharma
Sergey Redyuk
Sumantrak Mukherjee
Andrea Sipka
Eyke Hüllermeier
Sebastian Vollmer
David Selby
541
4
0
16 Jan 2024
Autotuning Apache TVM-based Scientific Applications Using Bayesian
  Optimization
Autotuning Apache TVM-based Scientific Applications Using Bayesian Optimization
Xingfu Wu
P. Paramasivam
Valerie Taylor
225
9
0
13 Sep 2023
Machine Learning-Assisted Discovery of Flow Reactor Designs
Machine Learning-Assisted Discovery of Flow Reactor Designs
Tom Savage
N. Basha
J. McDonough
James Krassowski
Omar K. Matar
Ehecatl Antonio del Rio Chanona
AI4CE
257
48
0
17 Aug 2023
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large
  Scales
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large ScalesConcurrency and Computation (CCPE), 2023
Xingfu Wu
Dali Wang
Michael Kruse
Jaehoon Koo
B. Videau
P. Hovland
V. Taylor
B. Geltz
Siddhartha Jana
Mary W. Hall
210
26
0
28 Mar 2023
BaCO: A Fast and Portable Bayesian Compiler Optimization Framework
BaCO: A Fast and Portable Bayesian Compiler Optimization FrameworkInternational Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2022
E. Hellsten
Artur L. F. Souza
Johannes Lenfers
Rubens Lacouture
Olivia Hsu
Adel Ejjeh
Fredrik Kjolstad
Michel Steuwer
K. Olukotun
Luigi Nardi
260
31
0
01 Dec 2022
Multi-Fidelity Cost-Aware Bayesian Optimization
Multi-Fidelity Cost-Aware Bayesian OptimizationComputer Methods in Applied Mechanics and Engineering (CMAME), 2022
Zahra Zanjani Foumani
Mehdi Shishehbor
Amin Yousefpour
Ramin Bostanabad
162
67
0
04 Nov 2022
Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for
  Simulated Chemical Reactors
Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors
Tom Savage
N. Basha
Omar K. Matar
Ehecatl Antonio del Rio Chanona
AI4CE
172
5
0
31 Oct 2022
Reinforcement Learning with Automated Auxiliary Loss Search
Reinforcement Learning with Automated Auxiliary Loss SearchNeural Information Processing Systems (NeurIPS), 2022
Tairan He
Yuge Zhang
Kan Ren
Minghuan Liu
Che Wang
Weinan Zhang
Yuqing Yang
Dongsheng Li
310
18
0
12 Oct 2022
Multi-objective hyperparameter optimization with performance uncertainty
Multi-objective hyperparameter optimization with performance uncertaintyInternational Conferences on Optimization and Learning (ICCOL), 2022
A. Hernández
I. Nieuwenhuyse
Gonzalo Nápoles
97
2
0
09 Sep 2022
Naive Automated Machine Learning
Naive Automated Machine LearningMachine-mediated learning (ML), 2021
F. Mohr
Marcel Wever
251
19
0
29 Nov 2021
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter
  Optimization
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
Marius Lindauer
Katharina Eggensperger
Matthias Feurer
André Biedenkapp
Difan Deng
C. Benjamins
Tim Ruhopf
René Sass
Katharina Eggensperger
367
467
0
20 Sep 2021
YAHPO Gym -- An Efficient Multi-Objective Multi-Fidelity Benchmark for
  Hyperparameter Optimization
YAHPO Gym -- An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimization
Florian Pfisterer
Lennart Schneider
Julia Moosbauer
Martin Binder
J. Herbinger
365
63
0
08 Sep 2021
Mutation is all you need
Mutation is all you need
Lennart Schneider
Florian Pfisterer
Martin Binder
J. Herbinger
BDL
402
4
0
04 Jul 2021
Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization
  Pragmas Using Bayesian Optimization (extended version)
Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization (extended version)International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (SHPCS), 2020
Xingfu Wu
Michael Kruse
Dali Wang
H. Finkel
P. Hovland
V. Taylor
Mary W. Hall
183
41
0
27 Apr 2021
CATE: Computation-aware Neural Architecture Encoding with Transformers
CATE: Computation-aware Neural Architecture Encoding with TransformersInternational Conference on Machine Learning (ICML), 2021
Shen Yan
Kaiqiang Song
Z. Feng
Mi Zhang
301
35
0
14 Feb 2021
Squirrel: A Switching Hyperparameter Optimizer
Squirrel: A Switching Hyperparameter Optimizer
Noor H. Awad
Gresa Shala
Difan Deng
Neeratyoy Mallik
Matthias Feurer
...
Diederick Vermetten
Hao Wang
Carola Doerr
Marius Lindauer
Katharina Eggensperger
111
8
0
15 Dec 2020
Automatic deep learning for trend prediction in time series data
Automatic deep learning for trend prediction in time series data
Kouame Hermann Kouassi
Deshendran Moodley
AI4TS
61
1
0
17 Sep 2020
Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of
  Tabular NAS Benchmarks
Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks
Arber Zela
Julien N. Siems
Lucas Zimmer
Jovita Lukasik
Margret Keuper
Katharina Eggensperger
447
99
0
22 Aug 2020
Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and
  Robust AutoDL
Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL
Lucas Zimmer
Marius Lindauer
Katharina Eggensperger
MU
320
101
0
24 Jun 2020
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