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On the robustness of sparse counterfactual explanations to adverse perturbations., and . Artif. Intell., (March 2023)Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy., , , , , , , , , and 4 other author(s). CoRR, (2020)Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning., , , and . CoRR, (2022)The five Is: Key principles for interpretable and safe conversational AI., and . CIIS, page 50-54. ACM, (2021)Coefficient mutation in the gene-pool optimal mixing evolutionary algorithm for symbolic regression., and . GECCO Companion, page 2289-2297. ACM, (2022)Improving Model-Based Genetic Programming for Symbolic Regression of Small Expressions., , , and . Evol. Comput., 29 (2): 211-237 (2021)DAISY: An Implementation of Five Core Principles for Transparent and Accountable Conversational AI., and . Int. J. Hum. Comput. Interact., 39 (9): 1856-1873 (May 2023)Local Search is a Remarkably Strong Baseline for Neural Architecture Search., , , and . CoRR, (2020)An Analysis of the Ingredients for Learning Interpretable Symbolic Regression Models with Human-in-the-loop and Genetic Programming., , , , and . ACM Trans. Evol. Learn. Optim., 4 (1): 5:1-5:30 (March 2024)Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors., , , , and . GECCO, page 1395-1402. ACM, (2018)