Interpretable machine learning on tabular data has traditionally relied on fragmented rule-induction ecosystems, where distinct paradigms are used for discrete and continuous targets, and transparent post hoc explanation of unsupervised structures is rarely integrated under a single model class. This article presents a...
This paper analyzes structural relationships among established algorithms and identifies indications of research siloing, and provides a formal definition of scored rule sets, showing how they generalize classical rule-based models, and illustrating concrete transformations from logicGP, ExSTraCS, and CART representati...
Robin Nunkesser· International Conference on...· 2 citations
The case suggests that generative AI is especially useful when requirements are only partially formalized, yet objective feedback from tests, benchmarks, and model quality metrics is available, and the results suggest that AI-augmented development is a relevant topic for scientific software engineering.
Robin Nunkesser· International Conference on...· 0 citations
It is argued that agent-generated native reference implementations—small vertical prototypes built directly against the platform’s native APIs with the help of coding agents—make differential, layer-bisection debugging an economically viable default tactic in cross-platform development.
Robin Nunkesser· International Conference on...· 0 citations
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