| 2025 | GECCO | Call for Action: towards the next generation of symbolic regression benchmark. | Guilherme Seidyo Imai Aldeia, Hengzhe Zhang, Geoffrey F. Bomarito, Miles D. Cranmer, Alcides Fonseca, Bogdan Burlacu, William G. La Cava, Fabrcio Olivetti de Frana |
| 2024 | GECCO | Inexact Simplification of Symbolic Regression Expressions with Locality-sensitive Hashing. | Guilherme Seidyo Imai Aldeia, Fabrcio Olivetti de Frana, William G. La Cava |
| 2024 | GECCO | Minimum variance threshold for epsilon-lexicase selection. | Guilherme Seidyo Imai Aldeia, Fabrcio Olivetti de Frana, William G. La Cava |
| 2023 | GECCO | Optimizing fairness tradeoffs in machine learning with multiobjective meta-models. | William G. La Cava |
| 2022 | EUROGP | SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming. | Nuno M. Rodrigues, Joo E. Batista, William G. La Cava, Leonardo Vanneschi, Sara Silva |
| 2022 | GECCO | Lexicase selection. | Thomas Helmuth, William G. La Cava |
| 2022 | GECCO | A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmark. | Patryk Orzechowski, Pawel Renc, William G. La Cava, Jason H. Moore, Arkadiusz Sitek, Jaroslaw Was, Joost B. Wagenaar |
| 2022 | PPSN | Population Diversity Leads to Short Running Times of Lexicase Selection. | Thomas Helmuth, Johannes Lengler, William G. La Cava |
| 2021 | GECCO | Lexicase Selection. | Thomas Helmuth, William G. La Cava |
| 2020 | GECCO | Genetic programming approaches to learning fair classifiers. | William G. La Cava, Jason H. Moore |
| 2019 | AMIA | Interpretation of machine learning predictions for patient outcomes in electronic health records. | William G. La Cava, Christopher R. Bauer, Jason H. Moore, Sarah A. Pendergrass |
| 2019 | GECCO | Semantic variation operators for multidimensional genetic programming. | William G. La Cava, Jason H. Moore |
| 2019 | ICLR | Learning concise representations for regression by evolving networks of trees. | William G. La Cava, Tilak Raj Singh, James Taggart, Srinivas Suri, Jason H. Moore |
| 2018 | GECCO | An analysis of ϵ-lexicase selection for large-scale many-objective optimization. | William G. La Cava, Jason H. Moore |
| 2018 | GECCO | A multidimensional genetic programming approach for identifying epsistatic gene interactions. | William G. La Cava, Sara Silva, Kourosh Danai, Lee Spector, Leonardo Vanneschi, Jason H. Moore |
| 2018 | GECCO | Where are we now?: a large benchmark study of recent symbolic regression methods. | Patryk Orzechowski, William G. La Cava, Jason H. Moore |
| 2018 | PSB | Data-driven advice for applying machine learning to bioinformatics problems. | Randal S. Olson, William G. La Cava, Zairah Mustahsan, Akshay Varik, Jason H. Moore |
| 2017 | EUROGP | A General Feature Engineering Wrapper for Machine Learning Using \epsilon -Lexicase Survival. | William G. La Cava, Jason H. Moore |
| 2017 | GECCO | Ensemble representation learning: an analysis of fitness and survival for wrapper-based genetic programming methods. | William G. La Cava, Jason H. Moore |
| 2016 | GECCO | Epsilon-Lexicase Selection for Regression. | William G. La Cava, Lee Spector, Kourosh Danai |
| 2015 | GECCO | Genetic Programming with Epigenetic Local Search. | William G. La Cava, Thomas Helmuth, Lee Spector, Kourosh Danai |
| 2014 | GECCO | Evolving differential equations with developmental linear genetic programming and epigenetic hill climbing. | William G. La Cava, Lee Spector, Kourosh Danai, Matthew Lackner |