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06/30/2023
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems
Performance complementarity of solvers available to tackle black-box opt...
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06/29/2023
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms
The L_∞ star discrepancy is a measure for the regularity of a finite set...
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06/27/2023
Heuristic Approaches to Obtain Low-Discrepancy Point Sets via Subset Selection
Building upon the exact methods presented in our earlier work [J. Comple...
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06/18/2023
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts
Extending a recent suggestion to generate new instances for numerical bl...
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06/08/2023
DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems
The application of machine learning (ML) models to the analysis of optim...
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06/07/2023
Self-Adjusting Weighted Expected Improvement for Bayesian Optimization
Bayesian Optimization (BO) is a class of surrogate-based, sample-efficie...
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06/01/2023
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances
In black-box optimization, it is essential to understand why an algorith...
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05/31/2023
Assessing the Generalizability of a Performance Predictive Model
A key component of automated algorithm selection and configuration, whic...
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05/30/2023
Sensitivity Analysis of RF+clust for Leave-one-problem-out Performance Prediction
Leave-one-problem-out (LOPO) performance prediction requires machine lea...
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03/08/2023
Using Affine Combinations of BBOB Problems for Performance Assessment
Benchmarking plays a major role in the development and analysis of optim...
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03/02/2023
Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB
Bayesian Optimization (BO) is a class of black-box, surrogate-based heur...
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02/23/2023
Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions
In a seminal paper in 2013, Witt showed that the (1+1) Evolutionary Algo...
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02/23/2023
Using Automated Algorithm Configuration for Parameter Control
Dynamic Algorithm Configuration (DAC) tackles the question of how to aut...
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01/24/2023
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms
Empirical data plays an important role in evolutionary computation resea...
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01/23/2023
RF+clust for Leave-One-Problem-Out Performance Prediction
Per-instance automated algorithm configuration and selection are gaining...
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11/21/2022
Explainable Model-specific Algorithm Selection for Multi-Label Classification
Multi-label classification (MLC) is an ML task of predictive modeling in...
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11/17/2022
Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis
Bayesian optimization (BO) algorithms form a class of surrogate-based he...
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11/02/2022
PI is back! Switching Acquisition Functions in Bayesian Optimization
Bayesian Optimization (BO) is a powerful, sample-efficient technique to ...
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09/09/2022
Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration
Algorithm selection wizards are effective and versatile tools that autom...
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09/09/2022
Fast Re-Optimization of LeadingOnes with Frequent Changes
In real-world optimization scenarios, the problem instance that we are a...
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05/07/2022
Automated Algorithm Selection for Radar Network Configuration
The configuration of radar networks is a complex problem that is often p...
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04/28/2022
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis
Bayesian Optimization (BO) is a surrogate-based global optimization stra...
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04/27/2022
Run Time Analysis for Random Local Search on Generalized Majority Functions
Run time analysis of evolutionary algorithms recently makes significant ...
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04/25/2022
SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison
Fair algorithm evaluation is conditioned on the existence of high-qualit...
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04/20/2022
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features
Per-instance algorithm selection seeks to recommend, for a given problem...
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04/20/2022
Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms
The stochastic nature of iterative optimization heuristics leads to inhe...
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04/15/2022
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants
Selecting the most suitable algorithm and determining its hyperparameter...
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04/13/2022
Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points
Dynamic algorithm selection can be beneficial for solving numerical blac...
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04/13/2022
Trajectory-based Algorithm Selection with Warm-starting
Landscape-aware algorithm selection approaches have so far mostly been r...
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03/17/2022
Non-Elitist Selection among Survivor Configurations can Improve the Performance of Irace
Modern optimization strategies such as evolutionary algorithms, ant colo...
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02/07/2022
Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration
It has long been observed that the performance of evolutionary algorithm...
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11/07/2021
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics
We present IOHexperimenter, the experimentation module of the IOHprofile...
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06/11/2021
Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance
Finding the best configuration of algorithms' hyperparameters for a give...
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04/24/2021
OPTION: OPTImization Algorithm Benchmarking ONtology
Many platforms for benchmarking optimization algorithms offer users the ...
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04/22/2021
Personalizing Performance Regression Models to Black-Box Optimization Problems
Accurately predicting the performance of different optimization algorith...
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04/19/2021
The Impact of Hyper-Parameter Tuning for Landscape-Aware Performance Regression and Algorithm Selection
Automated algorithm selection and configuration methods that build on ex...
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02/25/2021
Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules
Introducing new algorithmic ideas is a key part of the continuous improv...
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02/23/2021
Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms
With the goal to provide absolute lower bounds for the best possible run...
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02/12/2021
Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection
A key challenge in the application of evolutionary algorithms in practic...
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02/12/2021
Towards Large Scale Automated Algorithm Design by Integrating Modular Benchmarking Frameworks
We present a first proof-of-concept use-case that demonstrates the effic...
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02/10/2021
Towards Feature-Based Performance Regression Using Trajectory Data
Black-box optimization is a very active area of research, with many new ...
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02/09/2021
Optimal Static Mutation Strength Distributions for the (1+λ) Evolutionary Algorithm on OneMax
Most evolutionary algorithms have parameters, which allow a great flexib...
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02/01/2021
Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions
Facilitated by the recent advances of Machine Learning (ML), the automat...
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01/19/2021
Star Discrepancy Subset Selection: Problem Formulation and Efficient Approaches for Low Dimensions
Motivated by applications in instance selection, we introduce the star d...
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12/15/2020
Squirrel: A Switching Hyperparameter Optimizer
In this short note, we describe our submission to the NeurIPS 2020 BBO c...
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10/08/2020
Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking
Existing studies in black-box optimization suffer from low generalizabil...
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09/30/2020
Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes
Automated per-instance algorithm selection and configuration have shown ...
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07/08/2020
IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic
We propose IOHanalyzer, a new software for analyzing the empirical perfo...
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07/07/2020
Benchmarking in Optimization: Best Practice and Open Issues
This survey compiles ideas and recommendations from more than a dozen re...
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07/02/2020