DPC: Screening Methods for Sparse Models via Dual Projection onto Convex Set

This package implements the highly effective screening rules — developed under the DPC framework —  for many popular sparse learning models, like Lasso, non-negative Lasso, group Lasso, sparse-group Lasso etc.

  • Features including

    • highly effective in reducing the data size by discarding the irrelevant variables

    • highly effective in speeding up any existing algorithms for solving the sparse learning models

    • extremely efficient in dealing with big data problems

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