GALAHAD: Geometry-Adaptive Lyapunov-Assured Hybrid Optimizer
Implements the GALAHAD algorithm (Geometry-Adaptive
'Lyapunov'-Assured Hybrid Optimizer), combining 'Riemannian' metrics,
'Lyapunov' stability checks, and trust-region methods for stable
optimization of mixed-geometry parameters. Designed for biological
modeling (germination, dose-response, survival) where rates,
concentrations, and unconstrained variables coexist. Developed at
the Minnesota Center for Prion Research and Outreach (MNPRO),
University of Minnesota. Based on Conn et al. (2000)
<doi:10.1137/1.9780898719857>, Amari (1998)
<doi:10.1162/089976698300017746>, Beck & Teboulle (2003)
<doi:10.1016/S0167-6377(02)00231-6>, Nesterov (2017)
<https://www.jstor.org/stable/resrep30722>, and Walne et al. (2020)
<doi:10.1002/agg2.20098>.
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