Using the doubling dimension to analyze the generalization of learning algorithms-Reference-Cited by-同舟云学术

Using the doubling dimension to analyze the generalization of learning algorithms

Published:2009-09 Issue:6 Volume:75 Page:323-335
ISSN:0022-0000
Container-title:Journal of Computer and System Sciences
language:en
Short-container-title:Journal of Computer and System Sciences

Author:

Bshouty Nader H.,Li Yi,Long Philip M.

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Networks and Communications,Theoretical Computer Science

Reference36 articles.

1. K. Alexander, Rates of growth for weighted empirical processes, in: Proc. of Berkeley Conference in Honor of Jerzy Neyman and Jack Kiefer, vol. 2, 1985, pp. 475–493

2. Neural Network Learning: Theoretical Foundations;Anthony,1999

3. Plongements lipschitziens dans Rn;Assouad;Bull. Soc. Math. France,1983

4. Local Rademacher complexities;Bartlett;Ann. Statist.,2005

5. Prediction, learning, uniform convergence, and scale-sensitive dimensions;Bartlett;J. Comput. System Sci.,1998

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On Reporting Durable Patterns in Temporal Proximity Graphs;Proceedings of the ACM on Management of Data;2024-05-10

2. Optimal PAC Bounds without Uniform Convergence;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06

3. Non-uniform packings;Information Processing Letters;2022-03

4. Fast classification rates without standard margin assumptions;Information and Inference: A Journal of the IMA;2021-04-12

5. When are epsilon-nets small?;Journal of Computer and System Sciences;2020-06