Back to Results
First PageMeta Content
K-means clustering / Support vector machine / K-nearest neighbor algorithm / Linear classifier / Random forest / Naive Bayes classifier / Pattern recognition / Cross-validation / Classification rule / Statistics / Machine learning / Statistical classification


Efficient Learning on Point Sets Liang Xiong, Barnab´as P´oczos, and Jeff Schneider School of Computer Science Carnegie Mellon University Email: {lxiong,bapoczos,jeff.schneider}@cs.cmu.edu Abstract—Recently several m
Add to Reading List

Document Date: 2014-09-10 18:52:46


Open Document

File Size: 439,20 KB

Share Result on Facebook

Company

Neural Information Processing Systems / /

Currency

ZAR / /

/

Facility

Nanjing University / /

IndustryTerm

subsequent learning algorithms / above algorithms / pre-processing step / approximate search algorithm / set learning algorithms / search trees / set-based learning algorithms / computer vision algorithms / approximate solution / data less sensitive to different algorithms / social network / even approximate search / text processing / learning algorithm / learning algorithms / search algorithms / search methods / /

Organization

Nanjing University / National Science Foundation / Point Sets Liang Xiong / Barnab´as P´oczos / and Jeff Schneider School of Computer Science Carnegie Mellon University Email / Department of Computer Science & Technology / Pattern Analysis and Machine Intelligence / /

ProgrammingLanguage

php / /

PublishedMedium

Machine Learning / /

Technology

learning algorithm / subsequent learning algorithms / above algorithms / three algorithms / k-Means algorithm / computer vision algorithms / resulting algorithm / artificial intelligence / search algorithms / set learning algorithms / approximate search algorithm / clustering algorithm / http / Data Mining / machine learning / set-based learning algorithms / condensing algorithms / approximate NN search algorithms / /

URL

http /

SocialTag