Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

标题
Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering
作者
关键词
Attributed graph clustering, Model selection, Dirichlet process, Factorized information criterion
出版物
KNOWLEDGE AND INFORMATION SYSTEMS
Volume 53, Issue 1, Pages 239-268
出版商
Springer Nature
发表日期
2017-02-16
DOI
10.1007/s10115-017-1030-8

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Add your recorded webinar

Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.

Upload Now