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» Learning Generative Models with the Up-Propagation Algorithm
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125
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FGR
2004
IEEE
127views Biometrics» more  FGR 2004»
15 years 6 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
15 years 3 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
122
Voted
WWW
2005
ACM
16 years 3 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
15 years 4 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»
15 years 2 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