Sandia National Laboratories

# adapt_rank

Activate adaptive procedure for determining best rank representation

Specification

- Alias: None

- Arguments: None

- Default: false

Description

The adaptive algorithm proceeds as follows:

1. Start from rank `start_rank` and form an approximation

2. Adapt the current approximation by searching for a solution with lower rank that achieves L2 accuracy within epsilon tolerance of the reference.

3. If a lower rank solution is found with comparable accuracy, then stop. If not, increase the rank by an amount specified by `kick_rank`.

4. Return to step 2 and continue until either `max_rank` is reached or a converged rank (rank less than current reference with comparable accuracy) is found.

Default Behavior

No cross validation for rank.

Examples

This example shows specification of a rank adaptation starting at rank 2, incrementing by 2, and limited at rank 10.

    model,
     id_model = 'FT'
     surrogate global function_train
       start_order = 5
       adapt_rank  start_rank = 2  kick_rank = 2  max_rank = 10
       solver_tolerance   = 1e-12
       rounding_tolerance = 1e-12
     dace_method_pointer = 'SAMPLING'

Note that `adapt_rank` and `adapt_order` can either be combined or used separately.

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