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PAMI
2011
13 years 23 days ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
ICML
2010
IEEE
13 years 6 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
NIPS
2007
13 years 7 months ago
People Tracking with the Laplacian Eigenmaps Latent Variable Model
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
Zhengdong Lu, Miguel Á. Carreira-Perpi&ntil...
COLING
2010
13 years 24 days ago
A Discriminative Latent Variable-Based "DE" Classifier for Chinese-English SMT
Syntactic reordering on the source-side is an effective way of handling word order differences. The (DE) construction is a flexible and ubiquitous syntactic structure in Chinese w...
Jinhua Du, Andy Way
CVPR
2008
IEEE
14 years 7 months ago
Context and observation driven latent variable model for human pose estimation
Current approaches to pose estimation and tracking can be classified into two categories: generative and discriminative. While generative approaches can accurately determine human...
Abhinav Gupta, Trista Chen, Francine Chen, Don Kim...