Collapsed Variational Bayesian Inference for Hidden Markov Models by Wang, P, Blunsom, P

Stochastic collapsed variational inference for hidden Markov models by Wang, P, Blunsom, P

“…In this paper, we propose a stochastic collapsed variational inference algorithm for hidden Markov models, in a sequential data setting. Given a collapsed hidden Markov Model, we break its long Markov chain into a set of short subchains. …”

Collapsed Variational Bayesian Inference for Hidden Markov Models by Wang, P, Blunsom, P

A Hierarchical Pitman-Yor Process HMM for Unsupervised Part of Speech Induction. by Blunsom, P, Cohn, T

“…We develop a novel hidden Markov model incorporating sophisticated smoothing using a hierarchical Pitman-Yor processes prior, providing an elegant and principled means of incorporating lexical characteristics. …”

Stochastic collapsed variational inference for sequential data by Wang, P, Blunsom, P

“…Our algorithm is applicable to both finite hidden Markov models and hierarchical Dirichlet process hidden Markov models, and to any datasets generated by emission distributions in the exponential family. …”

Collapsed variational inference for computational linguistics by Wang, P

“…First, we solve a number of inference challenges arising from the hidden variable dependencies and derive a set of new CVI algorithms for the two ubiquitous and foundational models in computational linguistics, namely hidden Markov models (HMMs) and probabilistic context free grammars. …”