3 papers
cs.CC2026
NP-hardness of p-adic linear regression
Gregory D. Baker
-adic linear regression is the problem of finding coefficients that minimise . We prove that computing an optimal solution is NP-hard via a pol…
cs.LG2025
It's 2025 -- Narrative Learning is the new baseline to beat for explainable machine learning
Gregory D. Baker
In this paper, we introduce Narrative Learning, a methodology where models are defined entirely in natural language and iteratively refine their classification criteria using expla…
cs.LG2025
Linear Regression in p-adic metric spaces
Gregory D. Baker, Scott McCallum, Dirk Pattinson
Many real-world machine learning problems involve inherently hierarchical data, yet traditional approaches rely on Euclidean metrics that fail to capture the discrete, branching na…