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TSP
2010
13 years 3 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
CVPR
2011
IEEE
13 years 4 months ago
Tracking 3D Human Pose with Large Root Node Uncertainty
Representing articulated objects as a graphical model has gained much popularity in recent years, often the root node of the graph describes the global position and orientation of...
Ben Daubney, Xianghua Xie
DICTA
2008
13 years 10 months ago
Image Reconstruction from Contrast Information
An iterative algorithm for the reconstruction of natural images given only their contrast map is presented. The solution is neuro-physiologically inspired, where the retinal cells...
Asim A. Khwaja, Roland Goecke
UAI
2000
13 years 10 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
AIPS
2009
13 years 9 months ago
Efficient Solutions to Factored MDPs with Imprecise Transition Probabilities
When modeling real-world decision-theoretic planning problems in the Markov decision process (MDP) framework, it is often impossible to obtain a completely accurate estimate of tr...
Karina Valdivia Delgado, Scott Sanner, Leliane Nun...