| Document Date: 2003-04-11 14:26:30
Open Document File Size: 181,63 KBShare Result on Facebook
Company MICHAEL KEARNS AT&T Laboratories / AT&T Laboratories / / Currency USD / / / Event Product Issues / / IndustryTerm polynomial-time learning algorithm / noise-tolerant algorithm / statistical query algorithms / error-tolerant algorithms / randomized learning algorithms / noise-tolerant algorithms / noise-tolerant learning algorithms / sought algorithms / model algorithms / statistical query algorithm / learning algorithm / learning algorithms / / OperatingSystem PrEX / / Organization Association for Computing Machinery / / Person M. Finally / / Position Author / model / General / / Product Eq / oracle EX CN / / ProgrammingLanguage L / / ProvinceOrState New Jersey / / PublishedMedium Journal of the ACM / / Technology no noise-tolerant algorithm / statistical query algorithms / learning algorithm / noise-tolerant learning algorithms / noise-tolerant algorithm / error-tolerant algorithms / randomized learning algorithms / artificial intelligence / then sought algorithms / Valiant model algorithms / noise-tolerant algorithms / proposed algorithms / statistical query algorithm / Machine learning / simulation / polynomial-time learning algorithm / /
SocialTag |
Efficient Noise-Tolerant Learning from Statistical Queries MICHAEL KEARNS AT&T Laboratories—Research, Florham Park, New Jersey Abstract. In this paper, we study the problem of learning in the presence of classificatio