Papers


SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation
F. O. de Franca, M. Virgolin, M. Kommenda, M. S. Majumder, M. Cranmer, G. Espada, L. Ingelse, A. Fonseca, M. Landajuela, B. Petersen, R. Glatt, N. Mundhenk, C. S. Lee, J. D. Hochhalter, D. L. Randall, P. Kamienny, H. Zhang, G. Dick, A. Simon, B. Burlacu, Jaan Kasak, Meera Machado, Casper Wilstrup, W. G. La Cava (2024)
IEEE Transactions on Evolutionary Computation
Minimum variance threshold for epsilon-lexicase selection
Guilherme Seidyo Imai Aldeia, Fabrício Olivetti De França, William G. La Cava (2024)
Proceedings of the Genetic and Evolutionary Computation Conference
Pediatric Electrocardiogram-Based Deep Learning to Predict Secundum Atrial Septal Defects
Joshua Mayourian, Robert Geggel, William G. La Cava, Sunil J. Ghelani, John K. Triedman (2024)
Pediatric Cardiology
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
Shan Chen, Jack Gallifant, Mingye Gao, Pedro Moreira, Nikolaj Munch, Ajay Muthukkumar, Arvind Rajan, Jaya Kolluri, Amelia Fiske, Janna Hastings, Hugo Aerts, Brian Anthony, Leo Anthony Celi, William G. La Cava, Danielle S. Bitterman (2024)
Preprint
Benchmarking mortality risk prediction from electrocardiograms
Platon Lukyanenko, Joshua Mayourian, Mingxuan Liu, John K. Triedman, Sunil J. Ghelani, William G. La Cava (2024)
Preprint
Intrapartum electronic fetal heart rate monitoring to predict acidemia at birth with the use of deep learning
Jennifer A. McCoy, Lisa D. Levine, Guangya Wan, Corey Chivers, Joseph Teel, William G. La Cava (2024)
American Journal of Obstetrics and Gynecology
Inexact Simplification of Symbolic Regression Expressions with Locality-sensitive Hashing
Guilherme Seidyo Imai Aldeia, Fabricio Olivetti de Franca, William G. La Cava (2024)
Proceedings of the Genetic and Evolutionary Computation Conference
Deep learning-based electrocardiogram analysis to predict biventricular dysfunction and dilation in congenital heart disease
Joshua Mayourian, Addison Gearhart, William G La Cava, John K. Triedman, Andrew J. Powell, Anne Marie Valente, Tal Geva, Sunil J. Ghelani (2024)
Journal of the American College of Cardiology
Pediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling
Joshua Mayourian, William G. La Cava, Akhil Vaid, Girish N. Nadkarni, Sunil J. Ghelani, Rebekah Mannix, Tal Geva, Audrey Dionne, Mark E. Alexander, Son Q. Duong, John K. Triedman (2024)
Circulation
Accuracy of deep learning models in interpreting intrapartum fetal monitoring to predict fetal acidemia
Jennifer A. McCoy, Guangya Wan, Lisa D. Levine, Joseph Teel, John Holmes, William G.. La Cava (2024)
American Journal of Obstetrics and Gynecology
Exploring SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming
Nuno M. Rodrigues, João E. Batista, William G La Cava, Leonardo Vanneschi, Sara Silva (2023)
SN Computer Science
Effects of Race and Gender Classifications on Atherosclerotic Cardiovascular Disease Risk Estimates for Clinical Decision-Making in a Cohort of Black Transgender Women
Tonia Poteat, Elle Lett, Ashleigh J. Rich, Huijun Jiang, Andrea L. Wirtz, Asa Radix, Sari L. Reisner, Alexander B. Harris, Jowanna Malone, William G. La Cava, Catherine R. Lesko, Kenneth H. Mayer, Carl G. Streed (2023)
Health Equity
Fair admission risk prediction with proportional multicalibration
William G. La Cava, Elle Lett, Guangya Wan (2023)
Proceedings of the Conference on Health, Inference, and Learning
A flexible symbolic regression method for constructing interpretable clinical prediction models
William G. La Cava, Paul C. Lee, Imran Ajmal, Xiruo Ding, Priyanka Solanki, Jordana B. Cohen, Jason H. Moore, Daniel S. Herman (2023)
npj Digital Medicine
Translating intersectionality to fair machine learning in health sciences
Elle Lett, William G. La Cava (2023)
Nature Machine Intelligence
Optimizing fairness tradeoffs in machine learning with multiobjective meta-models
William G. La Cava (2023)
Proceedings of the 2023 Genetic and Evolutionary Computation Conference (GECCO)
Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?
Amelia L. M. Tan, Emily J. Getzen, Meghan R. Hutch, Zachary H. Strasser, Alba Gutiérrez-Sacristán, Trang T. Le, Arianna Dagliati, Michele Morris, David A. Hanauer, Bertrand Moal, Clara-Lea Bonzel, William Yuan, Lorenzo Chiudinelli, Priam Das, Harrison G. Zhang, Bruce J. Aronow, Paul Avillach, Gabriel. A. Brat, Tianxi Cai, Chuan Hong, William G. La Cava, He Hooi Will Loh, Yuan Luo, Shawn N. Murphy, Kee Yuan Hgiam, Gilbert S. Omenn, Lav P. Patel, Malarkodi Jebathilagam Samayamuthu, Emily R. Shriver, Zahra Shakeri Hossein Abad, Byorn W. L. Tan, Shyam Visweswaran, Xuan Wang, Griffin M. Weber, Zongqi Xia, Bertrand Verdy, Qi Long, Danielle L. Mowery, John H. Holmes (2023)
Journal of Biomedical Informatics
SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming
Nuno M. Rodrigues, João E. Batista, William La Cava, Leonardo Vanneschi, Sara Silva (2022)
Genetic Programming
A comparative study of GP-based and state-of-the-art classifiers on a synthetic machine learning benchmark
Patryk Orzechowski, Paweł Renc, William La Cava, Jason H. Moore, Arkadiusz Sitek, Jaroslaw Wąs, Joost Wagenaar (2022)
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Population Diversity Leads to Short Running Times of Lexicase Selection
Thomas Helmuth, Johannes Lengler, William La Cava (2022)
Parallel Problem Solving from Nature
PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods
Joseph D Romano, Trang T Le, William La Cava, John T Gregg, Daniel J Goldberg, Praneel Chakraborty, Natasha L Ray, Daniel Himmelstein, Weixuan Fu, Jason H Moore (2022)
Bioinformatics
Contemporary Symbolic Regression Methods and their Relative Performance
William La Cava, Patryk Orzechowski, Bogdan Burlacu, Fabricio de Franca, Marco Virgolin, Ying Jin, Michael Kommenda, Jason Moore (2021)
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks
Lexicase Selection
Thomas Helmuth, William La Cava (2021)
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Controller design by symbolic regression
Kourosh Danai, William G. La Cava (2021)
Mechanical Systems and Signal Processing
Genetic programming approaches to learning fair classifiers
William La Cava, Jason H. Moore (2020)
Proceedings of the 2020 Genetic and Evolutionary Computation Conference
Benchmarking in Optimization: Best Practice and Open Issues
Thomas Bartz-Beielstein, Carola Doerr, Daan Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, William La Cava, Manuel Lopez-Ibanez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise (2020)
Preprint
Evaluating recommender systems for AI-driven biomedical informatics
William La Cava, Heather Williams, Weixuan Fu, Steve Vitale, Durga Srivatsan, Jason H Moore (2020)
Bioinformatics
Learning feature spaces for regression with genetic programming
William La Cava, Jason H. Moore (2020)
Genetic Programming and Evolvable Machines
Interpretation of machine learning predictions for patient outcomes in electronic health records
William La Cava, Christopher R. Bauer, Jason H. Moore, Sarah A. Pendergrass (2019)
AMIA Annual Symposium
Learning concise representations for regression by evolving networks of trees
William La Cava, Tilak Raj Singh, James Taggart, Srinivas Suri, Jason H. Moore (2019)
International Conference on Learning Representations
A probabilistic and multi-objective analysis of lexicase selection and epsilon-lexicase selection
William La Cava, Thomas Helmuth, Lee Spector, Jason H. Moore (2019)
Evolutionary Computation
Semantic variation operators for multidimensional genetic programming
William La Cava, Jason H. Moore (2019)
Proceedings of the Genetic and Evolutionary Computation Conference
Relaxations of lexicase parent selection
Lee Spector, William La Cava, Saul Shanabrook, Thomas Helmuth, Edward Pantridge (2018)
Genetic Programming Theory and Practice XV
Relief-based feature selection: Introduction and review
Ryan J. Urbanowicz, Melissa Meeker, William La Cava, Randal S. Olson, Jason H. Moore (2018)
Journal of Biomedical Informatics
An analysis of ϵ-lexicase selection for large-scale many-objective optimization
William La Cava, Jason H. Moore (2018)
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Behavioral search drivers and the role of elitism in soft robotics
William La Cava, Jason H. Moore (2018)
Artificial Life
Multidimensional genetic programming for multiclass classification
William La Cava, Sara Silva, Kourosh Danai, Lee Spector, Leonardo Vanneschi, Jason H. Moore (2018)
Swarm and Evolutionary Computation
Where are we now? A large benchmark study of recent symbolic regression methods
Patryk Orzechowski, William La Cava, Jason H. Moore (2018)
Proceedings of the 2018 Genetic and Evolutionary Computation Conference
Ensemble representation learning: an analysis of fitness and survival for wrapper-based genetic programming methods
William La Cava, Jason H Moore (2017)
GECCO '17: Proceedings of the 2017 Genetic and Evolutionary Computation Conference
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison
Randal S. Olson, William La Cava, Patryk Orzechowski, Ryan J. Urbanowicz, Jason H. Moore (2017)
BioData Mining
A System for Accessible Artificial Intelligence
Randal S Olson, Moshe Sipper, William La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu, John H Holmes, Jason H. Moore (2017)
Genetic Programming Theory and Practice XIV
Data-driven Advice for Applying Machine Learning to Bioinformatics Problems
Randal S. Olson, William La Cava, Zairah Mustahsan, Akshay Varik, Jason H. Moore (2017)
Pacific Symposium on Biocomputing (PSB)
Restructuring Controllers to Accommodate Plant Nonlinearities
William G. La Cava, Kushal Sahare, Kourosh Danai (2017)
Journal of Dynamic Systems, Measurement, and Control
A General Feature Engineering Wrapper for Machine Learning Using \epsilon -Lexicase Survival
William La Cava, Jason Moore (2017)
Genetic Programming
Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification
William La Cava, Sara Silva, Leonardo Vanneschi, Lee Spector, Jason Moore (2017)
Applications of Evolutionary Computation
Automatic Development and Adaptation of Concise Nonlinear Models for System Identification
William G. La Cava (2016)
Thesis
Epsilon-Lexicase Selection for Regression
William La Cava, Lee Spector, Kourosh Danai (2016)
Proceedings of the Genetic and Evolutionary Computation Conference 2016
Inference of compact nonlinear dynamic models by epigenetic local search
William La Cava, Kourosh Danai, Lee Spector (2016)
Engineering Applications of Artificial Intelligence
Automatic identification of wind turbine models using evolutionary multiobjective optimization
William La Cava, Kourosh Danai, Lee Spector, Paul Fleming, Alan Wright, Matthew Lackner (2016)
Renewable Energy
Gradient-based adaptation of continuous dynamic model structures
William G. La Cava, Kourosh Danai (2016)
International Journal of Systems Science