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O3.1.1 Random Feature Development: Phase 2 #215

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6 of 8 tasks
odunbar opened this issue May 4, 2023 · 0 comments
Open
6 of 8 tasks

O3.1.1 Random Feature Development: Phase 2 #215

odunbar opened this issue May 4, 2023 · 0 comments
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odunbar commented May 4, 2023 •
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Following Issue #164 and after the PR #194 is merged, there are some subsequent work packages to do:

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  2. interface for defining user-priors #228
  3. SVD truncation for vector RF #229
  4. Sample stage for GCM application #230
  5. Documentation (beyond API) and uncomment docs API #233
  8. add new examples/tests into buildkite pipeline #234
@odunbar odunbar changed the title Random Feature Implementation: Phase 2 Random Feature Development: Phase 2 May 4, 2023
@odunbar odunbar mentioned this issue May 5, 2023
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@odunbar odunbar mentioned this issue Jul 11, 2023
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@odunbar odunbar mentioned this issue Sep 13, 2023
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@odunbar odunbar changed the title Random Feature Development: Phase 2 O3.1 Random Feature Development: Phase 2 Sep 13, 2023
@odunbar odunbar changed the title O3.1 Random Feature Development: Phase 2 O3.1.1 Random Feature Development: Phase 2 Sep 13, 2023
bors bot added a commit that referenced this issue Oct 6, 2023
@bors @odunbar
Merge #220
d9f4d91 
220: [WIP] Refactor and extend RF interface for more flexible kernels.  r=odunbar a=odunbar

<!--- THESE LINES ARE COMMENTED -->
## Purpose 
Addresses  points in #215 In particular:
- Closes #228 
- Closes #229 
- Closes #230
<!--- One sentence to describe the purpose of this PR, refer to any linked issues:
#14 -- this will link to issue 14
Closes #2 -- this will automatically close issue 2 on PR merge
-->


## To-do
<!---  list of proposed tasks in the PR, move to "Content" on completion 
- Proposed task
--> 

## Content
<!---  specific tasks that are currently complete 
- Solution implemented
-->
- Adds MCMC stage into `examples/GCM` and improves running interface
- Adds Shrinkage estimation into cross-validation for RF hyperparameter optimization.
- Adds Kernel interface for RF, where one specifies either a `Separable` or `Nonseparable` Kernel followed by the structure of the covariance to be used to sample the features.
    - `Nonseparable(cov)`: define one covariance structure on the `p * d`-dim space,
    -  `Separable(in_cov,out_cov)`: define one `d`-dim covariance for inputs and one `p`-dim covariance for outputs
- Choose covariance structures for `cov`,`in_cov`,`out_cov` from 
    - `OneDimFactor()`: Must be selected for 1D covariances
    - `DiagonalFactor(eps)`: Diagonal covariance plus `eps*I` 
    - `CholeskyFactor(eps)`: Cholesky representation `L*L^T` plus eps*I` 
    - `LowRankFactor(rank, eps)`: Symmetric factorization `W*W^T` where `W = 1+UDU'` D diag, U rectangular, plus `eps*I`
    - `HierarchicalLowRankFactor(rank, eps)`: Symmetric factorization `W*W^T` where `W = 1+UXU'` U rectangular, plus `eps*I` X cholesky factored
- Rebalancing the loss function seems to get far more robust results for vector RF
 
<!---
Review checklist

I have:
- followed the codebase contribution guide: https://clima.github.io/ClimateMachine.jl/latest/Contributing/
- followed the style guide: https://clima.github.io/ClimateMachine.jl/latest/DevDocs/CodeStyle/
- followed the documentation policy: https://github.com/CliMA/policies/wiki/Documentation-Policy
- checked that this PR does not duplicate an open PR.

In the Content, I have included 
- relevant unit tests, and integration tests, 
- appropriate docstrings on all functions, structs, and modules, and included relevant documentation.

-->

----
- [ ] I have read and checked the items on the review checklist.


Co-authored-by: odunbar <[email protected]>
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