PETScML

On the Use of "Conventional" Unconstrained Minimization Solvers for Training Regression Problems in Scientific Machine Learning

Stefano Zampini, Senior Research Scientist, Hierarchical Computations on Manycore Architectures

Mar 13, 12:00 - 13:00

B9 L2 R2325

petsc PETScML machine learning

This talk introduces PETScML, a framework leveraging traditional second-order optimization solvers for use within scientific machine learning, demonstrating improved generalization capabilities over gradient-based methods routinely adopted in deep learning.