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Group Lasso with Overlaps: the Latent Group Lasso approach

Dev.to / 4/8/2026

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Key Points

  • The article presents a “Latent Group Lasso” approach for performing group lasso when groups overlap, addressing limitations of standard group lasso formulations.
  • It focuses on reformulating the overlapping-group regularization problem using latent variables to better capture structure in overlapping feature groups.
  • The method is positioned as a practical way to obtain sparse solutions while respecting group memberships even when features belong to multiple groups.
  • The write-up emphasizes the optimization/modeling perspective behind the latent-variable formulation and how it supports overlapping group penalties.

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