L1 Regularization Paths in Linear Models by Parametric Gaussian Message Passing
The work proposes two dual algorithms for computing L1 regularization paths in linear models by using parametric Gaussian message passing within state space models. These methods efficiently find exact regularization paths, which are crucial for solving parametric quadratic programming problems related to L1 penalties.