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Clean up existing entry points about moma HOT 3 OPEN

dataslingers avatar dataslingers commented on June 19, 2024
Clean up existing entry points

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Comments (3)

michaelweylandt avatar michaelweylandt commented on June 19, 2024

This is a great issue - thanks for opening!

Do you think it'd be possible to consolidate down to a single C++ entry point or is that too tricky to design?

As you mentioned in a recent email, it's tricky to have grid parameters and multi-rank solutions. (It's ok if it's a "grid" of a single parameter, but it's hard after that...) That might just be a thing we disallow until we can (someday) find a better fix.

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Banana1530 avatar Banana1530 commented on June 19, 2024

An update on current APIs' location.

Docs:
https://docs.google.com/document/d/1TM-VW6nR_8CjlLjJ3SrFF6nJVXjeMFD2jDfKOktgPJM/edit?usp=sharing

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Banana1530 avatar Banana1530 commented on June 19, 2024
Argument specification Function Use case
Specify all arguments explicitly sfpca sfpca.R sfpca(X, alpha_u = 1, alpha_v = 2, Omega_u = sec_diff_mat(n), Omega_v = diag(p), EPS = 1e-9, MAX_ITER = 1e+5)
Parameter values and penalty types are separated; algorithm precision settings are wrapped in moma_pg_settings() moma_svd, SFPCA$initialize ... moma_expose.R SFPCA$initialize(X, u_sparsity = lasso(), lambda_u = c(1,10), selection_str = "ggbg" )
Parameter values and selection method are absorbed in penalty types moma_sfpca, moma_twpca ... moma_sf*_wrapper.R moma_spca(X, u_sparse = moma_lasso(lambda = seq(0, 2, 0.2), select_scheme = "b") )

The above table summarizes ways to specify penalty arguments.

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