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» Monte Carlo Hierarchical Model Learning
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ICCV
2005
IEEE
14 years 10 months ago
Probabilistic Contour Extraction Using Hierarchical Shape Representation
In this paper, we address the issue of extracting contour of the object with a specific shape. A hierarchical graphical model is proposed to represent shape variations. A complex ...
Xin Fan, Chun Qi, Dequn Liang, Hua Huang
DATE
2009
IEEE
129views Hardware» more  DATE 2009»
14 years 3 months ago
Improved performance and variation modelling for hierarchical-based optimisation of analogue integrated circuits
A new approach in hierarchical optimisation is presented which is capable of optimising both the performance and yield of an analogue design. Performance and yield trade offs are ...
Sawal Ali, Li Ke, Reuben Wilcock, Peter Wilson
ATAL
2006
Springer
14 years 15 days ago
A hierarchical approach to efficient reinforcement learning in deterministic domains
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
ICML
2005
IEEE
14 years 9 months ago
Tempering for Bayesian C&RT
This paper concerns the experimental assessment of tempering as a technique for improving Bayesian inference for C&RT models. Full Bayesian inference requires the computation ...
Nicos Angelopoulos, James Cussens
ICML
2009
IEEE
14 years 9 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani