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Found 2 papers, 1 papers with code
High-dimensional regression with potential prior information on variable importance
Examples include ordering on the variables offered by their empirical variances (which is typically discarded through standardisation), the lag of predictors when fitting autoregressive models in time series settings, or the level of missingness of the variables.
Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties
We provide an algorithm for exact and efficient computation of the global minimum of the resulting nonconvex objective in the case with a single variable with potentially many levels, and use this within a block coordinate descent procedure in the multivariate case.
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