LEAST SQUARE REGRESSION WITH COEFFICIENT REGULARIZATION BY GRADIENT DESCENT

摘要

We propose a stochastic gradient descent algorithm for the least square regression withncoefficient regularization. An explicit expression of the solution via sampling operatornand empirical integral operator is derived. Learning rates are given in terms of thensuitable choices of the step sizes and regularization parameters.