Least-Square Regularized Regression in Compressed Domain

摘要

This paper considers the regularized learning algorithm associated with the least-square loss and compressed domain. The target is the error analysis for the regression problem learned in compressed domain. We show that the least-square regularized algorithm is beneficial from the compressed sensing.