%0 Journal Article %1 Yao2007 %A Yao, Yuan %A Rosasco, Lorenzo %A Caponnetto, Andrea %D 2007 %J Constructive Approximation %K descent early gradient learning stopping %N 2 %P 289--315 %R 10.1007/s00365-006-0663-2 %T On Early Stopping in Gradient Descent Learning %U https://doi.org/10.1007/s00365-006-0663-2 %V 26 %X In this paper we study a family of gradient descent algorithms to approximate the regression function from reproducing kernel Hilbert spaces (RKHSs), the family being characterized by a polynomial decreasing rate of step sizes (or learning rate). By solving a bias-variance trade-off we obtain an early stopping rule and someprobabilistic upper bounds for the convergence of the algorithms. We also discuss the implication of these results in the context of classification where some fast convergence rates can be achieved for plug-in classifiers. Some connections are addressed with Boosting, Landweber iterations, and the online learning algorithms as stochastic approximations of the gradient descent method.

@article{Yao2007, abstract = {In this paper we study a family of gradient descent algorithms to approximate the regression function from reproducing kernel Hilbert spaces (RKHSs), the family being characterized by a polynomial decreasing rate of step sizes (or learning rate). By solving a bias-variance trade-off we obtain an early stopping rule and someprobabilistic upper bounds for the convergence of the algorithms. We also discuss the implication of these results in the context of classification where some fast convergence rates can be achieved for plug-in classifiers. Some connections are addressed with Boosting, Landweber iterations, and the online learning algorithms as stochastic approximations of the gradient descent method.}, added-at = {2018-06-03T18:28:46.000+0200}, author = {Yao, Yuan and Rosasco, Lorenzo and Caponnetto, Andrea}, biburl = {https://www.bibsonomy.org/bibtex/21662c2bc35a51078d5f7050fdd038fff/nosebrain}, day = 01, description = {On Early Stopping in Gradient Descent Learning | SpringerLink}, doi = {10.1007/s00365-006-0663-2}, interhash = {f126c01138716334467dbd1c04cc8263}, intrahash = {1662c2bc35a51078d5f7050fdd038fff}, issn = {1432-0940}, journal = {Constructive Approximation}, keywords = {descent early gradient learning stopping}, month = aug, number = 2, pages = {289--315}, timestamp = {2018-06-03T18:28:46.000+0200}, title = {On Early Stopping in Gradient Descent Learning}, url = {https://doi.org/10.1007/s00365-006-0663-2}, volume = 26, year = 2007 }