We develop a statistical framework for the simultaneous, unsupervised segmentation and discovery of visual object categories from image databases. Examining a large set of manuall...
From conventional wisdom and empirical studies of annotated data, it has been shown that visual statistics such as object frequencies and segment sizes follow power law distributi...
Alex Shyr, Trevor Darrell, Michael Jordan, Raquel ...
One of the important approaches for Knowledge discovery and Data mining is to estimate unobserved variables because latent variables can indicate hidden and specific properties o...
We present an approximation to the Bayesian hierarchical PitmanYor process language model which maintains the power law distribution over word tokens, while not requiring a comput...
In this paper, we propose a new application of Bayesian language model based on Pitman-Yor process for information retrieval. This model is a generalization of the Dirichlet distr...