Modifying iterated Laplace approximations
Methodology
2015-09-23 v1 Machine Learning
Abstract
In this paper, several modifications are introduced to the functional approximation method iterLap to reduce the approximation error, including stopping rule adjustment, proposal of new residual function, starting point selection for numerical optimisation, scaling of Hessian matrix. Illustrative examples are also provided to show the trade-off between running time and accuracy of the original and modified methods.
Keywords
Cite
@article{arxiv.1509.06492,
title = {Modifying iterated Laplace approximations},
author = {Tiep Mai and Simon Wilson},
journal= {arXiv preprint arXiv:1509.06492},
year = {2015}
}