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Author

Jaime Aguilar-Ortiz

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Open access Sep 2026

Cayley–Hamilton-Guided Krylov Regularization for Machine Learning: Theory, Computational Architecture, and Empirical Evidence

This study develops and evaluates a Cayley–Hamilton-based framework for regularised machine learning. Its objective is to formulate a practical Krylov-subspace architecture for classification that replaces repeated dense inversion with stable operator iteration. The formulation draws on the theorem’s finite polynomial...

Jaime Aguilar-Ortiz · 0 citations
#small language model Open access Sep 2026

Comparative Benchmark of Eleven Regression Models for Software Effort Estimation on a COCOMO-Like Dataset

This study develops a comparative benchmark for software effort estimation using the benchmark suite implemented in Python and the result package generated by that suite. Eleven regressors were compared under a leakage-safe protocol on a COCOMO-like dataset of 62 projects and 20 numeric predictors, with 49 projects res...

Jaime Aguilar-Ortiz, Víctor M. Zamudio-García, Marcos Yamir Gómez-Ramos et al. · 0 citations

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