Unclaimed author profile

David M. Blei

· Princeton University

Is this your research profile?

Create or sign in to your KnowledgeTrend account to claim this page. After the claim, this same profile URL and its linked publications will belong to your account. Claiming does not automatically grant a verified badge.

Create account and claim this profile Sign in to claim

2Linked publications

0Citations

0h-index

0i10-index

Metrics are calculated from publications currently linked to this profile.

Researcher overview

About

David M. Blei is a registered researcher in their academic field.

Research output

Recent Publications

2 research works linked to this profile

▤

Topic Modeling, Natural Language Processing Techniques, Web Data Mining and Analysis · 2012 · Communications of the ACM

Probabilistic topic models

David M. Blei

Surveying a suite of algorithms that offer a solution to managing large document archives.

ViewFull file not uploaded

▤

Natural Language Processing Techniques, Topic Modeling, Bayesian Methods and Mixture Models · 2003 · Journal of Machine Learning Research

Latent dirichlet allocation

David M. Blei, Andrew Y. Ng, Michael I. Jordan

We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is, in turn, modeled as an infinite mixture over an underlying set of topic probabilities. In the context of text modeling, the topic probabilities provide an explicit representation of a document. We present efficient approximate inference techniques based on variational methods and an EM algorithm for empirical Bayes parameter estimation. We report results in document modeling, text classification, and collaborative filtering, comparing to a mixture of unigrams model and the probabilistic LSI model.

ViewFull file not uploaded