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Moore, Jason H.

  1. Contemporary Symbolic Regression Methods and their Relative Performance
    2021/07/29 by William La Cava, La Cava, William, Patryk Orzechowski +13 · 48 citations
    Computer Science · #Evolutionary Algorithms and Applications #Metaheuristic Optimization Algorithms Research #Neural Networks and Applications
  2. Evaluation of a Tree-based Pipeline Optimization Tool for Automating\n Data Science
    2016/03/20 by Randal S. Olson, Olson, Randal S., Nathan Bartley +5 · 16 citations
    Computer Science · #Advanced Multi-Objective Optimization Algorithms #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Metaheuristic Optimization Algorithms Research #Neural and Evolutionary Computing (cs.NE)
  3. PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison
    2017/03/01 by Olson, Randal S., La Cava, William, Orzechowski, Patryk +2 · 14 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  4. Benchmarking in Optimization: Best Practice and Open Issues
    2020/07/07 by Bartz-Beielstein, Thomas, Doerr, Carola, Berg, Daan van den +14 · 9 citations
    #68W50 #A.1 #Applications (stat.AP) #B.8.0 #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #G.4 #I.2.8 #Neural and Evolutionary Computing (cs.NE) #Optimization and Control (math.OC) #Performance (cs.PF)
  5. PMLB v1.0: An open source dataset collection for benchmarking machine\n learning methods
    2020/11/30 by Joseph D. Romano, Romano, Joseph D., Trang T. Le +17 · 6 citations
    Computer Science · Materials Science · #Explainable Artificial Intelligence (XAI) #Machine Learning and Data Classification #Machine Learning in Materials Science
  6. Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras
    2024/04/29 by Yu, Jun, Dai, Yutong, Liu, Xiaokang +14 · 8 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  7. Relief-Based Feature Selection: Introduction and Review
    2017/11/22 by Urbanowicz, Ryan J., Meeker, Melissa, LaCava, William +2 · 3 citations
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  8. Data-driven Advice for Applying Machine Learning to Bioinformatics\n Problems
    2017/08/08 by Randal S. Olson, William La Cava, Olson, Randal S. +7 · 2 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #FOS: Biological sciences #FOS: Computer and information sciences #Gene expression and cancer classification #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Machine Learning in Bioinformatics #Quantitative Methods (q-bio.QM)
  9. Learning concise representations for regression by evolving networks of trees
    2018/07/03 by La Cava, William, Singh, Tilak Raj, Taggart, James +2 · 2 citations
    #FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE)
  10. Benchmarking Relief-Based Feature Selection Methods for Bioinformatics\n Data Mining
    2017/11/22 by Ryan J. Urbanowicz, Urbanowicz, Ryan J., Randal S. Olson +8 · 1 citation
    Computer Science · Biochemistry, Genetics and Molecular Biology · #Evolutionary Algorithms and Applications #Gene expression and cancer classification #Metaheuristic Optimization Algorithms Research
  11. Interpretation of machine learning predictions for patient outcomes in electronic health records
    2019/03/14 by La Cava, William, Bauer, Christopher, Moore, Jason H. +1 · 1 citation
    #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  12. Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies
    2023/11/22 by Huang, Yu-Ning, Love, Michael I., Ronkowski, Cynthia Flaire +13 · 2 citations
    #Digital Libraries (cs.DL) #FOS: Computer and information sciences
  13. Benchmarking AutoML Frameworks for Disease Prediction Using Medical Claims
    2021/07/22 by Roland Albert A. Romero, Romero, Roland Albert A., Mariefel Nicole Y. Deypalan +11 · 1 citation
    Computer Science · Economics, Econometrics and Finance · Health Professions · #Artificial Intelligence in Healthcare #FOS: Computer and information sciences #Healthcare Systems and Reforms #Machine Learning (cs.LG) #Machine Learning in Healthcare
  14. Benchmarking AutoML algorithms on a collection of synthetic classification problems
    2022/12/06 by Ribeiro, Pedro Henrique, Orzechowski, Patryk, Wagenaar, Joost +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  15. Automating biomedical data science through tree-based pipeline\n optimization
    2016/01/28 by Randal S. Olson, Olson, Randal S., Ryan J. Urbanowicz +9 · 1 citation
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Advanced Multi-Objective Optimization Algorithms #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Machine Learning in Bioinformatics #Neural and Evolutionary Computing (cs.NE)
  16. A review of feature selection strategies utilizing graph data structures and knowledge graphs
    2024/06/21 by Sisi Shao, Pedro Henrique Ribeiro, Shao, Sisi +5 · 1 citation
    Computer Science · #Graph Theory and Algorithms #Advanced Graph Neural Networks
  17. Lexidate: Model Evaluation and Selection with Lexicase
    2024/06/17 by Jose Guadalupe Hernandez, Anil Kumar Saini, Hernandez, Jose Guadalupe +3 · 1 citation
    Computer Science · #Natural Language Processing Techniques #Semantic Web and Ontologies