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 | 426 | 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 | 250 | 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 | 200 | 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 | 125 | 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 | 65 | 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 | 41 | 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 | 38 | 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 | 34 | 2018 |
Text mining with hybrid biclustering algorithms P Orzechowski, K Boryczko International Conference on Artificial Intelligence and Soft Computing, 102-113, 2016 | 24 | 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 | 23 | 2018 |
Scalable biclustering—the future of big data exploration? P Orzechowski, K Boryczko, JH Moore GigaScience 8 (7), giz078, 2019 | 17 | 2019 |
Proximity measures and results validation in biclustering–a survey P Orzechowski Artificial Intelligence and Soft Computing: 12th International Conference …, 2013 | 17 | 2013 |
Propagation-based biclustering algorithm for extracting inclusion-maximal motifs P Orzechowski, K Boryczko Computing and Informatics 35 (2), 391-410, 2016 | 14 | 2016 |
Hybrid biclustering algorithms for data mining P Orzechowski, K Boryczko Applications of Evolutionary Computation: 19th European Conference …, 2016 | 14 | 2016 |
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 | 13 | 2022 |
EBIC: an open source software for high-dimensional and big data analyses P Orzechowski, JH Moore Bioinformatics 35 (17), 3181-3183, 2019 | 12 | 2019 |
Generative and reproducible benchmarks for comprehensive evaluation of machine learning classifiers P Orzechowski, JH Moore Science Advances 8 (47), eabl4747, 2022 | 10 | 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 | 10 | 2020 |
Effective biclustering on GPU-capabilities and constraints P Orzechowski, K Boryczko Prz Elektrotechniczn 1, 133-6, 2015 | 10 | 2015 |
Parallel approach for visual clustering of protein databases P Orzechowski, K Boryczko Computing and Informatics 29 (6+), 1221-1231, 2010 | 10 | 2010 |