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» Variational methods for Reinforcement Learning
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EMMCVPR
2007
Springer
14 years 1 months ago
Bottom-Up Recognition and Parsing of the Human Body
Recognizing humans, estimating their pose and segmenting their body parts are key to high-level image understanding. Because humans are highly articulated, the range of deformation...
Praveen Srinivasan, Jianbo Shi
WACV
2005
IEEE
14 years 1 months ago
Robust Salient Motion Detection with Complex Background for Real-Time Video Surveillance
Moving object detection is very important for video surveillance. In many environments, motion maybe either interesting (salient) motion (e.g., a person) or uninteresting motion (...
Ying-li Tian, Arun Hampapur
NIPS
1998
13 years 9 months ago
SMEM Algorithm for Mixture Models
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Ge...
WSC
1998
13 years 9 months ago
Integrating Neural Networks with Special Purpose Simulation
Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...
Dany Hajjar, Simaan M. AbouRizk, Kevin Mather
IPM
2008
196views more  IPM 2008»
13 years 7 months ago
Author identification: Using text sampling to handle the class imbalance problem
Authorship analysis of electronic texts assists digital forensics and anti-terror investigation. Author identification can be seen as a single-label multi-class text categorizatio...
Efstathios Stamatatos