|dc.description.abstract||Slice models are collections of mathematical programs with the same
structure but di erent data. Examples of slice models appear in Data
Envelopment Analysis, where they are used to evaluate e ciency, and
cross-validation, where they are used to measure generalization ability.
Because they involve multiple programs, slice models tend to be data-
intensive and time consuming to solve. However, by incorporating addi-
tional information in the solution process, such as the common structure
and shared data, we are able to solve these models much more e ciently.
In addition because of the e ciency we achieve, we are able to process
much larger real-world problems and extend slice model results through
the application of more computationally-intensive procedures.||en