Tuning as a Means of Assessing the Benefits of New Ideas in Interplay
with Existing Algorithmic Modules

Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules

25 February 2021

Diederick Vermetten

Thomas Bäck

Papers citing "Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules"

9 / 9 papers shown

Title
An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise Catalin-Viorel Dinu Yash J. Patel X. Bonet-Monroig Hao Wang 45 0 0 25 Sep 2024
LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics Niki van Stein Thomas Bäck 59 17 0 30 May 2024
Evolving the Structure of Evolution Strategies Sander van Rijn Hao Wang M. Leeuwen Thomas Bäck 61 56 0 17 Oct 2016
The CMA Evolution Strategy: A Tutorial N. Hansen 64 1,372 0 04 Apr 2016
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting N. Hansen A. Auger Raymond Ros Olaf Mersmann Tea Tušar D. Brockhoff 55 424 0 29 Mar 2016
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization Lisha Li Kevin Jamieson Giulia DeSalvo Afshin Rostamizadeh Ameet Talwalkar 222 2,325 0 21 Mar 2016
A Computationally Efficient Limited Memory CMA-ES for Large Scale Optimization I. Loshchilov ODL 52 88 0 21 Apr 2014
SPOT: An R Package For Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization Thomas Bartz-Beielstein 89 54 0 23 Jun 2010
CMA-ES with Two-Point Step-Size Adaptation Nikolaus Hansen 105 575 0 02 May 2008