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CVPR
1999
IEEE
16 years 6 months ago
Explaining Optical Flow Events with Parameterized Spatio-Temporal Models
A spatio-temporal representation for complex optical flow events is developed that generalizes traditional parameterized motion models (e.g. affine). These generative spatio-tempo...
Michael J. Black
ICML
2005
IEEE
16 years 4 months ago
Hierarchical Dirichlet model for document classification
The proliferation of text documents on the web as well as within institutions necessitates their convenient organization to enable efficient retrieval of information. Although tex...
Sriharsha Veeramachaneni, Diego Sona, Paolo Avesan...
ESSMAC
2003
Springer
15 years 9 months ago
Self-tuning Control of Non-linear Systems Using Gaussian Process Prior Models
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
Daniel Sbarbaro, Roderick Murray-Smith
NIPS
2008
15 years 5 months ago
Syntactic Topic Models
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
Jordan L. Boyd-Graber, David M. Blei
NIPS
2003
15 years 5 months ago
Ambiguous Model Learning Made Unambiguous with 1/f Priors
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...
Gurinder S. Atwal, William Bialek