Every day, an enormous amount of text data is produced. Sources of text data include news,
social media, emails, text messages, medical reports, scientific publications and fiction. To …

In topic models, collections are organized as documents where they arise as mixtures over
latent clusters called topics. A topic is a distribution over the vocabulary. In large-scale …

As an extension to the standard symmetric latent Dirichlet allocation topic model, we
implement asymmetric Beta-Liouville as a conjugate prior to the multinomial and therefore …

Nonparametric topic models based on hierarchical Dirichlet processes (HDPs) allow for the
number of topics to be automatically discovered from the data. The computational complexity …

Intrinsically, topic models have always their likelihood functions fixed to multinomial
distributions as they operate on count data instead of Gaussian data. As a result, their …