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» Learning Generative Models with the Up-Propagation Algorithm
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FGR
2004
IEEE
127views Biometrics» more  FGR 2004»
15 years 1 months ago
Gait Style and Gait Content: Bilinear Models for Gait Recognition Using Gait Re-sampling
Human Identification using gait is a challenging computer vision task due to the dynamic motion of gait and the existence of various sources of variations such as viewpoint, walki...
Chan-Su Lee, Ahmed M. Elgammal
LWA
2004
14 years 11 months ago
Modeling Rule Precision
This paper reports first results of an empirical study of the precision of classification rules on an independent test set. We generated a large number of rules using a general co...
Johannes Fürnkranz
WWW
2005
ACM
15 years 10 months ago
Ranking definitions with supervised learning methods
This paper is concerned with the problem of definition search. Specifically, given a term, we are to retrieve definitional excerpts of the term and rank the extracted excerpts acc...
Jun Xu, Yunbo Cao, Hang Li, Min Zhao
ECAI
2008
Springer
14 years 11 months ago
An Analysis of Bayesian Network Model-Approximation Techniques
Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...
Adamo Santana, Gregory M. Provan
PAMI
2008
179views more  PAMI 2008»
14 years 9 months ago
Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
A dynamic texture is a spatio-temporal generative model for video, which represents video sequences as observations from a linear dynamical system. This work introduces the mixtur...
Antoni B. Chan, Nuno Vasconcelos