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12/06/2022
Benchmarking AutoML algorithms on a collection of binary problems
Automated machine learning (AutoML) algorithms have grown in popularity ...
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10/24/2022
Applying Autonomous Hybrid Agent-based Computing to Difficult Optimization Problems
Evolutionary multi-agent systems (EMASs) are very good at dealing with d...
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07/29/2021
Contemporary Symbolic Regression Methods and their Relative Performance
Many promising approaches to symbolic regression have been presented in ...
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07/14/2021
Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers
Understanding the strengths and weaknesses of machine learning (ML) algo...
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05/03/2021
EBIC.JL – an Efficient Implementation of Evolutionary Biclustering Algorithm in Julia
Biclustering is a data mining technique which searches for local pattern...
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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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07/26/2018
EBIC: an open source software for high-dimensional and big data biclustering analyses
Motivation: In this paper we present the latest release of EBIC, a next-...
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04/25/2018
Where are we now? A large benchmark study of recent symbolic regression methods
In this paper we provide a broad benchmarking of recent genetic programm...
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01/09/2018
EBIC: an artificial intelligence-based parallel biclustering algorithm for pattern discovery
In this paper a novel biclustering algorithm based on artificial intelli...
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10/09/2017
Considerations of automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure
With the maturation of metabolomics science and proliferation of biobank...
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05/01/2017
