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» Learning Probabilistic Models of Relational Structure
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AAAI
2012
11 years 10 months ago
Advances in Lifted Importance Sampling
We consider lifted importance sampling (LIS), a previously proposed approximate inference algorithm for statistical relational learning (SRL) models. LIS achieves substantial vari...
Vibhav Gogate, Abhay Kumar Jha, Deepak Venugopal
IROS
2009
IEEE
132views Robotics» more  IROS 2009»
14 years 2 months ago
Automatic selection of task spaces for imitation learning
Abstract— Previous work [1] shows that the movement representation in task spaces offers many advantages for learning object-related and goal-directed movement tasks through imit...
Manuel Mühlig, Michael Gienger, Jochen J. Ste...
CIVR
2008
Springer
239views Image Analysis» more  CIVR 2008»
13 years 9 months ago
Analyzing Flickr groups
There is an explosion of community-generated multimedia content available online. In particular, Flickr constitutes a 200-million photo sharing system where users participate foll...
Radu Andrei Negoescu, Daniel Gatica-Perez
COLT
2010
Springer
13 years 5 months ago
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
CVPR
2005
IEEE
14 years 9 months ago
Hallucinating Faces: TensorPatch Super-Resolution and Coupled Residue Compensation
In this paper, we propose a new face hallucination framework based on image patches, which integrates two novel statistical super-resolution models. Considering that image patches...
Wei Liu, Dahua Lin, Xiaoou Tang