Patryk Orzechowski
Patryk Orzechowski
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Cited by
Cited by
PMLB: a large benchmark suite for machine learning evaluation and comparison
RS Olson, W La Cava, P Orzechowski, RJ Urbanowicz, JH Moore
BioData mining 10, 1-13, 2017
Contemporary symbolic regression methods and their relative performance
W La Cava, B Burlacu, M Virgolin, M Kommenda, P Orzechowski, ...
Advances in neural information processing systems 2021 (DB1), 1, 2021
Where are we now? A large benchmark study of recent symbolic regression methods
P Orzechowski, W La Cava, JH Moore
Proceedings of the genetic and evolutionary computation conference, 1183-1190, 2018
Benchmarking in optimization: Best practice and open issues
T Bartz-Beielstein, C Doerr, D Berg, J Bossek, S Chandrasekaran, ...
arXiv preprint arXiv:2007.03488, 2020
Mapping patient trajectories using longitudinal extraction and deep learning in the MIMIC-III critical care database
BK Beaulieu-Jones, P Orzechowski, JH Moore
Pacific symposium on biocomputing 2018: proceedings of the pacific symposium …, 2018
Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure
A Orlenko, JH Moore, P Orzechowski, RS Olson, J Cairns, PJ Caraballo, ...
PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018: Proceedings of the Pacific Symposium …, 2018
EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery
P Orzechowski, M Sipper, X Huang, JH Moore
Bioinformatics 34 (21), 3719-3726, 2018
A system for accessible artificial intelligence
RS Olson, M Sipper, WL Cava, S Tartarone, S Vitale, W Fu, ...
Genetic programming theory and practice XV, 121-134, 2018
Text mining with hybrid biclustering algorithms
P Orzechowski, K Boryczko
International Conference on Artificial Intelligence and Soft Computing, 102-113, 2016
runibic: a Bioconductor package for parallel row-based biclustering of gene expression data
P Orzechowski, A Pańszczyk, X Huang, JH Moore
Bioinformatics 34 (24), 4302-4304, 2018
Proximity measures and results validation in biclustering–a survey
P Orzechowski
Artificial Intelligence and Soft Computing: 12th International Conference …, 2013
Scalable biclustering—the future of big data exploration?
P Orzechowski, K Boryczko, JH Moore
GigaScience 8 (7), giz078, 2019
Propagation-based biclustering algorithm for extracting inclusion-maximal motifs
P Orzechowski, K Boryczko
Computing and Informatics 35 (2), 391-410, 2016
Hybrid biclustering algorithms for data mining
P Orzechowski, K Boryczko
Applications of Evolutionary Computation: 19th European Conference …, 2016
EBIC: an open source software for high-dimensional and big data analyses
P Orzechowski, JH Moore
Bioinformatics 35 (17), 3181-3183, 2019
Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers
P Orzechowski, JH Moore
Science Advances 8 (47), eabl4747, 2022
Benchmarking manifold learning methods on a large collection of datasets
P Orzechowski, F Magiera, JH Moore
Genetic Programming: 23rd European Conference, EuroGP 2020, Held as Part of …, 2020
Effective biclustering on GPU-capabilities and constraints
P Orzechowski, K Boryczko
Prz Elektrotechniczn 1, 133-6, 2015
Parallel approach for visual clustering of protein databases
P Orzechowski, K Boryczko
Computing and Informatics 29 (6+), 1221-1231, 2010
Artificial Intelligence for COVID-19 Detection in Medical Imaging—Diagnostic Measures and Wasting—A Systematic Umbrella Review
P Jemioło, D Storman, P Orzechowski
Journal of Clinical Medicine 11 (7), 2054, 2022
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