A fast tracking algorithm for generalized LARS/LASSO

This letter gives an efficient algorithm for tracking the solution curve of sparse logistic regression With respect to the L I regularization parameter. The algorithm is based on approximating the logistic regression loss by a piecewise quadratic function, using Rosset and Zhu's path tracking algorithm on the approximate problem, and then applying a correction to get to the true path. Application of the algorithm to text classification and sparse kernel logistic regression shows that the algorithm is efficient.