144 citations · 150 across the 5 of their papers we have counts for
8 papers
Applying Autonomous Hybrid Agent-based Computing to Difficult Optimization Problems
Mateusz Godzik, Jacek Dajda, Marek Kisiel-Dorohinicki +5
Evolutionary multi-agent systems (EMASs) are very good at dealing with difficult, multi-dimensional problems, their efficacy was proven theoretically based on analysis of the relev…
Contemporary Symbolic Regression Methods and their Relative Performance
William La Cava, Patryk Orzechowski, Bogdan Burlacu +5
Many promising approaches to symbolic regression have been presented in recent years, yet progress in the field continues to suffer from a lack of uniform, robust, and transparent…
Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers
Patryk Orzechowski, Jason H. Moore
Understanding the strengths and weaknesses of machine learning (ML) algorithms is crucial for determine their scope of application. Here, we introduce the DIverse and GENerative ML…
EBIC.JL -- an Efficient Implementation of Evolutionary Biclustering Algorithm in Julia
Paweł Renc, Patryk Orzechowski, Aleksander Byrski +2
Biclustering is a data mining technique which searches for local patterns in numeric tabular data with main application in bioinformatics. This technique has shown promise in multi…
Benchmarking in Optimization: Best Practice and Open Issues
Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg +14
This survey compiles ideas and recommendations from more than a dozen researchers with different backgrounds and from different institutes around the world. Promoting best practice…
Where are we now? A large benchmark study of recent symbolic regression methods
Patryk Orzechowski, William La Cava, Jason H. Moore
In this paper we provide a broad benchmarking of recent genetic programming approaches to symbolic regression in the context of state of the art machine learning approaches. We use…