Regularization is model styling |

**Jon Claerbout**

*Regularization* is a method used in mathematics and statistics
to deal with insufficient information.
The reader must supply additional information in the form of an operator.
From where is this operator to come, and what does it mean?
It amounts to us, as practitioners, specifying a ``style'' of model.
Where the model is a signal or an image,
it amounts to specifying one weighting function in physical space
and another in Fourier space.

- EMPTY BINS AND INVERSE INTERPOLATION

- WELLS NOT MATCHING THE SEISMIC MAP
- SEARCHING THE SEA OF GALILEE
- CODE FOR THE REGULARIZED SOLVER

- PRECONCEPTION AND CROSS VALIDATION
- About this document ...

2014-12-03