Back to Results
First PageMeta Content
Statistical classification / Regression analysis / Statistical theory / Supervised learning / Support vector machine / Dimension reduction / Loss function / Non-negative matrix factorization / Principal component analysis / Statistics / Machine learning / Multivariate statistics


Closed-Form Supervised Dimensionality Reduction with Generalized Linear Models Irina Rish IBM T.J. Watson Research Center, Yorktown Heights, NY[removed]USA
Add to Reading List

Document Date: 2009-08-10 09:51:56

Open Document

File Size: 212,44 KB

Share Result on Facebook

City

Pittsburgh / Helsinki / New York / /

Company

IBM / Future Work Lee D. D. / Iterative Update Rules / /

Country

Puerto Rico / Jordan / United States / Finland / /

Currency

pence / /

/

Facility

Princeton University / Carnegie Mellon University / Green Hall / /

IndustryTerm

performance management / potential applications / analytical solution / http /

OperatingSystem

XP / /

Organization

School of Computer Science / Royal Statistical Society / Generalized Linear Models Irina Rish IBM T.J. Watson Research Center / Princeton University / Carnegie Mellon University / /

Person

Sajama Orlitsky / Francisco Pereira / Alon Orlitsky / Geoff Gordon / Ynk / Genady Grabarnik / Guillermo Cecchi / /

/

Position

author / generalized linear model for principal component analysis / model / /

ProgrammingLanguage

L / /

ProvinceOrState

Pennsylvania / /

PublishedMedium

Journal of the Royal Statistical Society / Machine Learning / /

Technology

Proteomics / artificial intelligence / Machine Learning / SDR algorithms / EM-style algorithms / /

URL

http /

SocialTag