Exclusive Group Lasso for Structured Variable Selection. (arXiv:2108.10284v2 [cs.LG] UPDATED)

A structured variable selection problem is considered in which the
covariates, divided into predefined groups, activate according to sparse
patterns with few nonzero entries per group. Capitalizing on the concept of
atomic norm, a composite norm can be properly designed to promote such
exclusive group sparsity patterns. The resulting norm lends itself to efficient
and flexible regularized optimization algorithms for support recovery, like the
proximal algorithm. Moreover, an active set algorithm is proposed that builds
the solution by successively including …

arxiv concept exclusive lasso norm patterns per promote sparsity