Recursive ridge regression using second-order stochastic algorithms
Résumé
Recursive second-order stochastic algorithms are presented for solving ridge regression problems in the linear and binary logistic case. The proposed algorithms allow us to update the estimates of ridge solution when the data arrive in continuous flow. We establish the almost sure convergence with rate of proposed algorithms. Numerical experiments on simulated and real-world data show the advantages of our algorithms compared to alternative methods.
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