In recent years, the language model Latent Dirichlet Allocation (LDA), which clusters co-occurring words into topics, has been widely applied in the computer vision field. Howeve...
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...
This paper suggests an alternative solution for the task of spoken document retrieval (SDR). The proposed system runs retrieval on multi-level transcriptions (word and phone) prod...
Shan Jin, Hemant Misra, Thomas Sikora, Joemon M. J...
A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein familyor the columns of a multiple alignment of that famil...
Michael Brown, Richard Hughey, Anders Krogh, I. Sa...