13 search results - page 2 / 3 » On Nonparametric Predictive Inference for Ordinal Data |
CACM
2011
13 years 6 days ago
2011
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
ICDM
2008
IEEE
13 years 11 months ago
2008
IEEE
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...
AMDO
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. We propose a hierarchical process for inferring the 3D pose of a person from monocular images. First we infer a learned view-based 2D body model from a single image using...
AAAI
2008
13 years 7 months ago
2008
Matrix factorization algorithms are frequently used in the machine learning community to find low dimensional representations of data. We introduce a novel generative Bayesian pro...