Goto

Collaborating Authors

 Yuting Wei

Early stopping for kernel boosting algorithms: A general analysis with localized complexities

Neural Information Processing Systems

Early stopping of iterative algorithms is a widely-used form of regularization in statistics, commonly used in conjunction with boosting and related gradienttype algorithms. Although consistency results have been established in some settings, such estimators are less well-understood than their analogues based on penalized regularization.

Early stopping for kernel boosting algorithms: A general analysis with localized complexities

Neural Information Processing Systems

Neural Information Processing Systems http://nips.cc/