GraphicalModelLearning.jl
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Algorithms for Learning Graphical Models
Figure out a clean way to make regularizers parametric, for example `regularizer*sqrt(log((num_spins^2)/0.05)/num_samples)`.
Consider adding a generic `GMLFormulation`, which includes functions that plug into the bigger JuMP model. Then `RISE`, `logRISE`, `RPLE` would be specific instances of this generic formulation.
For now we assume discrete models. `(something)` indicates that `something` is optional, everything else is required. A Julia data-structure that can be serialized to JSON as follows, ``` { "variable_count":,...
In testings can correctness thresholds be set programmatically based on the number of samples?
Use the value of `gibbs_test_samples` to correctly set the settings of `isapprox` on inverse ising formulations regression test.