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

16 August 2019

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

9 / 9 papers shown

Title
Accel-NASBench: Sustainable Benchmarking for Accelerator-Aware NAS Afzal Ahmad Linfeng Du Zhiyao Xie Wei Zhang 18 0 0 09 Apr 2024
Explainable Benchmarking for Iterative Optimization Heuristics Niki van Stein Diederick Vermetten Anna V. Kononova Thomas Bäck 32 12 0 31 Jan 2024
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales Xingfu Wu Prasanna Balaprakash Michael Kruse Jaehoon Koo B. Videau P. Hovland V. Taylor B. Geltz Siddhartha Jana Mary W. Hall 32 12 0 28 Mar 2023
Multi-objective hyperparameter optimization with performance uncertainty A. Hernández I. Nieuwenhuyse Gonzalo Nápoles 19 2 0 09 Sep 2022
Naive Automated Machine Learning F. Mohr Marcel Wever 24 11 0 29 Nov 2021
Mutation is all you need Lennart Schneider Florian Pfisterer Martin Binder B. Bischl BDL 60 4 0 04 Jul 2021
Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization (extended version) Xingfu Wu Michael Kruse Prasanna Balaprakash H. Finkel P. Hovland V. Taylor Mary W. Hall 34 32 0 27 Apr 2021
CATE: Computation-aware Neural Architecture Encoding with Transformers Shen Yan Kaiqiang Song Z. Feng Mi Zhang 22 24 0 14 Feb 2021
Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL Lucas Zimmer Marius Lindauer Frank Hutter MU 14 90 0 24 Jun 2020