3 papers
math.NA2026
A Twin gradient method for unconstrained optimization
Anna De Magistris, Michiel E. Hochstenbach, Gerardo Toraldo
We propose a new strategy for gradient-based unconstrained optimization, involving two parallel sequences of iterates that cooperate to determine their stepsizes via a \textit{Twin…
stat.ME2025
An algorithm for a constrained P-spline
Rosanna Campagna, Serena Crisci, Gabriele Santin +2
Regression splines are largely used to investigate and predict data behavior, attracting the interest of mathematicians for their beautiful numerical properties, and of statisticia…
stat.ME2024
Roughness regularization for functional data analysis with free knots spline estimation
Anna De Magistris, Valentina De Simone, Elvira Romano +1
In the era of big data, an ever-growing volume of information is recorded, either continuously over time or sporadically, at distinct time intervals. Functional Data Analysis (FDA)…