"Unsupervised learning"

A Practical Algorithm for Topic Modeling with Provable Guarantees

Topic models provide a useful method for dimensionality reduction and exploratory data analysis in large text corpora. Most approaches to topic model learning have been based on a maximum likelihood objective. Efficient algorithms exist that attempt …

Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests

We give a polynomial-time algorithm for provably learning the structure and parameters of bipartite noisy-or Bayesian networks of binary variables where the top layer is completely hidden. Unsupervised learning of these models is a form of discrete …

Unsupervised Learning of Noisy-Or Bayesian Networks

This paper considers the problem of learning the parameters in Bayesian networks of discrete variables with known structure and hidden variables. Previous approaches in these settings typically use expectation maximization; when the network has high …