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» On the Entropy of a Hidden Markov Process
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JMLR
2010
202views more  JMLR 2010»
13 years 3 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
CORR
2010
Springer
168views Education» more  CORR 2010»
13 years 6 months ago
Gaussian Process Structural Equation Models with Latent Variables
In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by...
Ricardo Silva
ICIP
2003
IEEE
14 years 10 months ago
Deformable face mapping for person identification
This paper introduces a novel deformable model for face mapping and its application to automatic person identification. While most face recognition techniques directly model the f...
Florent Perronnin, Jean-Luc Dugelay, Kenneth Rose
ICIP
2003
IEEE
14 years 10 months ago
Techniques for automatic video content derivation
In this paper, we focus on the use of three different techniques that support automatic derivation of video content from raw video data, namely, a spatio-temporal rule-based metho...
Milan Petkovic, Vojkan Mihajlovic, Willem Jonker
ICIP
2002
IEEE
14 years 10 months ago
Parametric contour tracking using unscented Kalman filter
This paper presents an efficient method to integrate various spatial-temporal constraints to regularize the contour tracking. The global shape of the contour is represented in a p...
Yunqiang Chen, Thomas S. Huang, Yong Rui