Back to Results
First PageMeta Content
Dirichlet process / Hidden Markov model / Mixture model / Expectation–maximization algorithm / Information retrieval / Dirichlet distribution / Normal distribution / Semantic similarity / Kullback–Leibler divergence / Statistics / Machine learning / Natural language processing


CONTENT-BASED MUSICAL SIMILARITY COMPUTATION USING THE HIERARCHICAL DIRICHLET PROCESS Matthew Hoffman Princeton University Dept. of Computer Science
Add to Reading List

Document Date: 2015-03-12 00:16:21


Open Document

File Size: 168,56 KB

Share Result on Facebook

City

information retrieval / Vienna / London / New York / /

Company

Cambridge University Press / B. Bayesian Data Analysis CRC Press / /

Country

Jordan / Austria / Canada / United Kingdom / /

EntertainmentAwardEvent

the South by Southwest / South by Southwest / /

Facility

Princeton University / /

IndustryTerm

metal / k-means algorithm / metal songs / analogous algorithm / simpler algorithm / /

MusicGroup

South by Southwest / /

Organization

Cambridge University / G20 / Wellcome Department of Cognitive Neurology / American Statistical Association / GHz Intel Core Duo / Princeton University / Computer Science Department / /

Person

David Blei / George Tzanetakis / /

Position

SXSW artist / artist / /

Product

Pentax K-x Digital Camera / /

ProvinceOrState

British Columbia / New York / Victoria / /

PublishedMedium

Journal of the American Statistical Association / /

Region

Southwest / /

Technology

analogous algorithm / RAM / k-means algorithm / HDP-based algorithms / HDP-based algorithm / GMM-based algorithms / G1 algorithm / Duo processor / unsupervised algorithm / E-M algorithm / G1C algorithm / 3.3 VQ Codebook This algorithm / much simpler algorithm / PDF / using an unsupervised algorithm / /

URL

http /

SocialTag