Back to Results
First PageMeta Content
Learning / Artificial intelligence / Regularization / Limited-memory BFGS / Support vector machine / Solid modeling / Hinge loss / Orthant-wise limited-memory quasi-Newton / Machine learning / Statistics / Statistical classification


L1 AND L2 REGULARIZATION FOR MULTICLASS HINGE LOSS MODELS Robert C. Moore and John DeNero Google Research
Add to Reading List

Document Date: 2013-09-11 11:03:38


Open Document

File Size: 368,91 KB

Share Result on Facebook

City

Sapporo / Corvallis / Edmonton / Prague / Philadelpha / Helsinki / /

Company

Wall Street Journal / Penn Treebank / MALLET / Google / /

Country

Japan / United States / Canada / Finland / Czech Republic / /

IndustryTerm

statistical natural language processing / iterative line search method / typical natural language processing classification problem / natural-language processing / cyclic dependency network / /

Organization

Association of Computational Linguistics / North American Chapter / Association for Computational Linguistics / /

Person

Giorgio Satta / John DeNero / Aravind K. Joshi / Robert C. Moore / Thomas Finley / Thorsten Joachims / Bush / Libin Shen / Percy Liang / Jorge Nocedal / Stephen J. Wright / Mitchell P. Marcus / Dan Klein / Kristina Toutanova / Jianfeng Gao / Galen Andrew / Christopher D. Manning / Beatrice Santorini / Yoram Singer / Hal Daum / Chun-Nam John Yu / Franz Josef Och / Mary A. Marcinkiewicz / Andrew McCallum / /

Position

Singer / /

ProvinceOrState

Alberta / Pennsylvania / Oregon / /

PublishedMedium

Computational Linguistics / Machine Learning / Journal of Machine Learning Research / Wall Street Journal / /

Technology

natural language processing / machine translation / LEARNING ALGORITHMS / Data Mining / Machine Learning / /

URL

http /

SocialTag