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Evolutionary Computation|May 11, 2018
A Probabilistic and Multi-Objective Analysis of Lexicase Selection and -Lexicase SelectionWilliam La Cava, Thomas Helmuth, Lee Spector, et al.Genetic and Evolutionary Computation Conference : [Proceedings]. Genetic and Evolutionary Computation Conference|July 18, 2022
Semantic variation operators for multidimensional genetic programmingWilliam La Cava, Jason H MooreGenetic Programming and Evolvable Machines|December 21, 2020
Learning feature spaces for regression with genetic programmingWilliam La Cava, Jason H MooreArtificial Life|September 2, 2021
Problem-Solving Benefits of Down-Sampled Lexicase SelectionThomas Helmuth, Lee SpectorAMIA ... Annual Symposium Proceedings. AMIA Symposium|April 21, 2020
Interpretation of machine learning predictions for patient outcomes in electronic health recordsWilliam La Cava, Christopher Bauer, Jason H Moore, et al.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 9, 2017
Data-driven advice for applying machine learning to bioinformatics problemsRandal S Olson, William La Cava, Zairah Mustahsan, et al.Biodata Mining|December 15, 2017
PMLB: a large benchmark suite for machine learning evaluation and comparisonRandal S Olson, William La Cava, Patryk Orzechowski, et al.Bioinformatics (Oxford, England)|August 9, 2020
Evaluating recommender systems for AI-driven biomedical informaticsWilliam La Cava, Heather Williams, Weixuan Fu, et al.Journal of Biomedical Informatics|July 22, 2018
Relief-based feature selection: Introduction and reviewRyan J Urbanowicz, Melissa Meeker, William La Cava, et al.Advances in Neural Information Processing Systems|May 8, 2024
Contemporary Symbolic Regression Methods and their Relative PerformanceWilliam La Cava, Bogdan Burlacu, Marco Virgolin, et al.Pageof 50