Model-Based Genetic Algorithms for Algorithm Configuration, Proc. of International Conf. on Artificial Intelligence (IJCAI'15). AAAI, pp.733-739, 2015. ,
Experimental Methods for the Analysis of Optimization Algorithms, 2010. ,
SPOT: A Toolbox for Interactive and Automatic Tuning in the R Environment, Proc. of the 20th Workshop Computational Intelligence. Universitätsverlag Karlsruhe, pp.264-273, 2010. ,
Feature Based Algorithm Configuration: A Case Study with Differential Evolution, Proc. of the 14th International Conference on Parallel Problem Solving from Nature (PPSN XIV) (Lecture Notes in Computer Science, vol.9921, pp.156-166, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01359539
Surrogate Assisted Feature Computation for Continuous Problems, Proc. of Learning and Intelligent Optimization (LION'16), vol.10079, pp.17-31, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01303320
Per Instance Algorithm Configuration of CMA-ES with Limited Budget, Proc. of the 19th Annual Conference on Genetic and Evolutionary Computation (GECCO), 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01613753
, , pp.681-688
smoof: Single-and Multi-Objective Optimization Test Functions, The R Journal, 2017. ,
Hyper-Heuristics: A Survey of the State of the Art, Journal of the Operational Research Society, vol.64, pp.1695-1724, 2013. ,
Hyper-Parameter Tuning for the (1 + (?, ?)) GA, Proc. of the 21st Annual Conference on Genetic and Evolutionary Computation (GECCO'19), 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02175766
The Compound Random Search, Ph.D. Dissertation. Purdue University, 1972. ,
The Choice of Step Length, a Crucial Factor in the Performance of Variable Metric Algorithms, Numerical Methods for Non-Linear Optimization, pp.149-170, 1972. ,
Optimal Static and Self-Adjusting Parameter Choices for the (1 + (?, ?)) Genetic Algorithm, Algorithmica, vol.80, pp.1658-1709, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01668262
Theory of Parameter Control Mechanisms for Discrete Black-Box Optimization: Provable Performance Gains Through Dynamic Parameter Choices, Theory of Randomized Search Heuristics in Discrete Search Spaces, 2018. ,
From Black-Box Complexity to Designing New Genetic Algorithms, Theoretical Computer Science, vol.567, pp.87-104, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01272858
Self-Adjusting Mutation Rates with Provably Optimal Success Rules, Proc. of the 21st Annual Conference on Genetic and Evolutionary Computation (GECCO'19), 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02175768
Mutation Rate Matters Even When Optimizing Monotonic Functions, Evolutionary Computation, vol.21, pp.1-27, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-01086549
On the Effectiveness of Simple Success-Based Parameter Selection Mechanisms for Two Classical Discrete Black-Box Optimization Benchmark Problems, Proc. of the 20th Annual Conference on Genetic and Evolutionary Computation (GECCO'18), pp.943-950, 2018. ,
Sensitivity of Parameter Control Mechanisms with Respect to Their Initialization, International Conference on Parallel Problem Solving from Nature (PPSN'18), vol.11102, pp.360-372, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01921055
Hyperparameter Optimization, Automated Machine Learning: Methods, Systems, Challenges, pp.3-38, 2019. ,
Optimization of Control Parameters for Genetic Algorithms, IEEE Trans. on Systems, Man, and Cybernetics, vol.16, pp.122-128, 1986. ,
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01294124
Real-Parameter Black-Box Optimization Benchmarking 2009: Noiseless Functions Definitions, 2009. ,
URL : https://hal.archives-ouvertes.fr/inria-00362633
flaccogui: Exploratory Landscape Analysis for Everyone, Proc. of the Genetic and Evolutionary Computation Conference Companion (GECCO'17), pp.1215-1222, 2017. ,
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms, International Conference on Principles and Practice of Constraint Programming, pp.213-228, 2006. ,
Sequential Model-Based Optimization for General Algorithm Configuration, Proc. of Learning and Intelligent Optimization (LION'11), pp.507-523, 2011. ,
Parameter Control in Evolutionary Algorithms: Trends and Challenges, IEEE Transactions on Evolutionary Computation, vol.19, pp.167-187, 2015. ,
Automated Algorithm Selection: Survey and Perspectives, Evolutionary Computation, vol.27, pp.3-45, 2019. ,
Cell Mapping Techniques for Exploratory Landscape Analysis, EVOLVE -A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp.115-131, 2014. ,
Detecting Funnel Structures by Means of Exploratory Landscape Analysis, Proc. of the 17th Annual Conference on Genetic and Evolutionary Computation (GECCO'15), pp.265-272, 2015. ,
Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models, Proc. of the 18th Annual Conference on Genetic and Evolutionary Computation (GECCO'16), 2016. ,
Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning, Evolutionary Computation, vol.27, pp.99-127, 2019. ,
A General Dichotomy of Evolutionary Algorithms on Monotone Functions, International Conference on Parallel Problem Solving from Nature (PPSN'18), vol.11102, pp.3-15, 2018. ,
Learning the Empirical Hardness of Optimization Problems: The Case of Combinatorial Auctions, Principles and Practice of Constraint Programming-CP 2002, pp.556-572, 2002. ,
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization, Journal of Machine Learning Research, vol.18, 2017. ,
2007. Parameter Setting in Evolutionary Algorithms, Studies in Computational Intelligence, vol.54 ,
The irace package: Iterated Racing for Automatic Algorithm Configuration, Operations Research Perspectives, vol.3, pp.43-58, 2016. ,
Exploratory Landscape Analysis, Proc. of the 13th Annual Conference on Genetic and Evolutionary Computation (GECCO'11), pp.829-836, 2011. ,
, Performance Analysis of Continuous Black-Box Optimization Algorithms via Footprints in Instance Space, Evolutionary Computation (ECJ), vol.25, pp.529-554, 2017.
Algorithm Configuration Landscapes: -More Benign Than Expected, International Conference on Parallel Problem Solving from Nature (PPSN'18), vol.11102, pp.271-283, 2018. ,
Evolutionary Optimization of Low-Discrepancy Sequences, ACM Transactions on Modeling and Computer Simulation, vol.22, pp.1-9, 2012. ,
Exploring the MLDA Benchmark on the Nevergrad Platform, Proc. of the 21st Annual Conference on Genetic and Evolutionary Computation, 2019. ,
Nevergrad -A Gradient-Free Optimization Platform, 2018. ,
, Ingo Rechenberg. 1973. Evolutionsstrategie. Friedrich Fromman Verlag (Günther Holzboog KG)
Adaptive Step Size Random Search, IEEE Transactions on Automatic Control, vol.13, pp.270-276, 1968. ,
Evolving the Structure of Evolution Strategies, Proc. of IEEE Symposium Series on Computational Intelligence (SSCI'16), 2016. ,