GAP Safe Screening Rules for Sparse-Group Lasso

NeurIPS 2016 Eugene NdiayeOlivier FercoqAlexandre GramfortJoseph Salmon

For statistical learning in high dimension, sparse regularizations have proven useful to boost both computational and statistical efficiency. In some contexts, it is natural to handle more refined structures than pure sparsity, such as for instance group sparsity... (read more)

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