Reparameterisation
Reparameterization is a technique used in various fields, including machine learning and optimization, to transform the parameters of a model or function into a different set of parameters. This transformation can simplify the optimization process, improve numerical stability, or enable the use of specific optimization algorithms. The key idea is to re-express the original parameters in terms of new parameters, which may have different properties or constraints.
In machine learning, reparameterization is often used in variational inference and generative models. For example, in
Reparameterization can also be applied in optimization problems to transform the objective function into a more
The choice of reparameterization depends on the specific problem and the desired properties of the new parameters.