Open AccessProceedings Article
Sequential Parameter Optimization
Thomas Bartz-Beielstein
- 01 Jan 2009
- pp 0
298
TL;DR: Although sequential parameter optimization relies on enhanced statistical techniques such as design and analysis of computer experiments, it can be performed algorithmically and requires basically the specification of the relevant algorithm's parameters.
read more
Abstract: We provide a comprehensive, effective and very efficient methodology for the design and experimental analysis of algorithms.
We rely on modern statistical techniques for tuning and understanding algorithms
from an experimental perspective. Therefore, we make use of the sequential parameter optimization (SPO) method that has been successfully applied as a tuning procedure to numerous heuristics for practical and theoretical
optimization problems.
Two case studies, which illustrate the applicability of SPO to algorithm tuning
and model selection, are presented.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A mixed integer linear programming model for reliability optimisation in the component deployment problem
TL;DR: A mixed integer linear programming (MILP) formulation of the component deployment problem is presented and results show that the MILP solver is efficient in finding feasible solutions even where other methods fail, or prove infeasibility where feasible solutions do not exist.
A Literature Survey on Offline Automatic Algorithm Configuration
TL;DR: This paper briefly explains the automatic algorithm configuration problem, then surveys the automated methods developed to handle this problem and argued about their main advantages and disadvantages to help researchers or practitioners select the best possible method for their specific problem.
Automated Algorithm Configuration and Design
Leslie Pérez Cáceres,Manuel López Ibáñez,Thomas Stützle +2 more
- 15 Jul 2023
TL;DR: Leslie Pérez Cáceres is an associated professor at Pontificia Universidad Católica de Valparáıso, Chile and the Director of the Artificial Intelligence Diploma of the PUCV’s Escuela the Ingenieŕıa Informática.
Efficient global optimization for combinatorial problems
Martin Zaefferer,Jörg Stork,Martina Friese,Andreas Fischbach,Boris Naujoks,Thomas Bartz-Beielstein +5 more
- 12 Jul 2014
TL;DR: It is shown for the first time that EGO can successfully be applied to combinatorial optimization problems and clearly outperforms the competing approaches on most of the tested problem instances.
An experimental investigation of model-based parameter optimisation: SPO and beyond
Frank Hutter,Holger H. Hoos,Kevin Leyton-Brown,Kevin Murphy +3 more
- 08 Jul 2009
TL;DR: A new version of SPO is proposed, dubbed SPO+, which extends SPO with a novel intensification procedure and log-transformed response values, and it is demonstrated that SPO+ achieves state-of-the-art performance.
References
•Book
Applied Regression Analysis
Norman R. Draper,Harry Smith +1 more
- 01 Jan 1966
TL;DR: In this article, the Straight Line Case is used to fit a straight line by least squares, and the Durbin-Watson Test is used for checking the straight line fit.
19K
A new optimizer using particle swarm theory
Russell C. Eberhart,James Kennedy +1 more
- 04 Oct 1995
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
16.4K
•Journal Article
The Design and Analysis of Experiments
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
15.2K
R: A Language for Data Analysis and Graphics
Ross Ihaka,Robert Gentleman +1 more
TL;DR: In this article, the authors discuss their experience designing and implementing a statistical computing language, which combines what they felt were useful features from two existing computer languages, and they feel that the new language provides advantages in the areas of portability, computational efficiency, memory management, and scope.
10.9K