the New York Times / Neural Information Processing Systems / Andrew / Ge / Twitter / Mei / Rethinking LDA / Donnelly / Stephens / /
Country
Jordan / United States / China / /
Event
Product Issues / Product Recall / /
Facility
Peking University / University of Michigan / University of Michigan Abstract Topic / /
IndustryTerm
inference algorithm / matrix factorization algorithms / inference algorithms / mining / media using topic models / data mining tasks / web-based articles / /
Organization
Department of EECS / University of Michigan Abstract Topic / National Science Foundation / Doctoral Fund / Department of Statistics / University of Michigan / School of Information / U.S. Securities and Exchange Commission / School of EECS / senate / Peking University / National Natural Science Foundation of China / deD / Ministry of Education / /
Person
David M. Collaborative / Daniel A. Topic / Michael I. Latent Dirichlet / Brian D. Empirical / Edwin V / David M. Relative / / /
Position
model for political texts /
Product
error / /
ProgrammingLanguage
K / D / /
ProvinceOrState
New York / Michigan / /
PublishedMedium
Machine Learning / New York Times / the New York Times / /
Technology
inference algorithms / two inference algorithms / API / inference algorithm / machine learning / knowledge management / data mining / simulation / genotype / matrix factorization algorithms / /
Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis Jian Tang1 TANGJIAN @ NET. PKU . EDU . CN Zhaoshi Meng2