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» A probabilistic language based on sampling functions
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ICDAR
2007
IEEE
15 years 4 months ago
Energy-Based Models in Document Recognition and Computer Vision
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
CVPR
2003
IEEE
15 years 11 months ago
Variational Inference for Visual Tracking
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Jaco Vermaak, Neil D. Lawrence, Patrick Pér...
ICDE
2010
IEEE
212views Database» more  ICDE 2010»
14 years 10 months ago
Cleansing uncertain databases leveraging aggregate constraints
— Emerging uncertain database applications often involve the cleansing (conditioning) of uncertain databases using additional information as new evidence for reducing the uncerta...
Haiquan Chen, Wei-Shinn Ku, Haixun Wang
JMLR
2012
13 years 3 days ago
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
We consider the task of estimating, from observed data, a probabilistic model that is parameterized by a finite number of parameters. In particular, we are considering the situat...
Michael Gutmann, Aapo Hyvärinen
COMPGEOM
2009
ACM
15 years 4 months ago
Integral estimation from point cloud in d-dimensional space: a geometric view
Integration over a domain, such as a Euclidean space or a Riemannian manifold, is a fundamental problem across scientific fields. Many times, the underlying domain is only acces...
Chuanjiang Luo, Jian Sun, Yusu Wang