Back to Results
First PageMeta Content
Multivariate statistics / Data mining / Machine learning / Linear algebra / Matrix theory / Spectral clustering / Cluster analysis / Kernel principal component analysis / K-means clustering / Statistics / Mathematics / Algebra


Efficient Kernel Clustering Using Random Fourier Features Radha Chitta, Rong Jin and Anil K. Jain Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA [removed], r
Add to Reading List

Document Date: 2012-10-17 14:03:01


Open Document

File Size: 160,55 KB

Share Result on Facebook

City

Kernel / East Lansing / /

Company

Manning Publications Co. / Neural Information Processing Systems / Knowledge-Based Intelligent Engineering Systems / Allied Technologies / Microsoft / /

Country

United States / /

/

Facility

Michigan State University / University of Oxford / University of Texas / /

IndustryTerm

spectral clustering algorithms / information processing / medical imaging / spatial data mining / inner product / linear learning algorithms / kernel-based learning algorithm / recommendation systems / monte-carlo algorithms / clustering algorithms / dot product / data mining / multiprocessor systems / earlier kernel-based algorithms / linear clustering algorithms / data mining task / k-means algorithm / linear clustering algorithm / spectral clustering algorithm / baseline algorithms / data mining research community / proposed clustering algorithms / approximate solution / web search / mining / linear learning algorithm / kernel clustering algorithms / proposed clustering algorithm / conventional clustering algorithms / large scale nearest neighbor search / kmeans algorithm / learning algorithms / /

MusicGroup

The Network / /

NaturalFeature

Forest CoverType / Forest Cover Type SV / /

OperatingSystem

XP / /

Organization

Michigan State University / US Forest Service / office of Naval Research / University of Texas at Austin / National Academy of Sciences / University of Oxford / VLDB Endowment / Anil K. Jain Department of Computer Science and Engineering / Pattern Analysis and Machine Intelligence / /

Person

G. W. Stewart / A. Prodromidis / S. Stolfo / P. Chan / W. Lee / C. Ranger / J. Guang Sun / Anil K. Jain / R. Raghuraman / A. Penmetsa / Rong Jin / G. Bradski / W. Fan / C. Kozyrakis / /

Position

Ranger / /

ProgrammingLanguage

C / /

ProvinceOrState

Texas / Michigan / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / Journal of the ACM / Machine Learning / Proceedings of the National Academy of Sciences / /

Technology

kernel-based algorithms / SV clustering algorithm / RAM / linear learning algorithm / proposed clustering algorithm / clustering algorithms / remaining algorithms / clustering algorithm / kmeans algorithm / proposed algorithms / 4 We Algorithm / Machine Learning / Kernel clustering algorithms / monte-carlo algorithms / linear clustering algorithms / 2.8 GHz processor / two algorithms / runtime Algorithm / linear clustering algorithm / kernel-based learning algorithm / k-means algorithm / linear learning algorithms / baseline algorithms / RFF clustering algorithm / conventional clustering algorithms / gene expression / spectral clustering algorithms / proposed clustering algorithms / spectral clustering algorithm / data mining / B. Baseline algorithms / earlier kernel-based algorithms / matrix H. Algorithm / medical imaging / using an efficient linear clustering algorithm / /

URL

http /

SocialTag