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» On Learning with Integral Operators
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JELIA
2004
Springer
16 years 4 days ago
Two Approaches to Merging Knowledge Bases
We present a framework for expressing different merging operators for belief sets. This framework is a generalisation of our earlier work concerning consistency-based belief revisi...
James P. Delgrande, Torsten Schaub
NMR
2004
Springer
16 years 3 days ago
Consistency-based approaches to merging knowledge bases: preliminary report
We present a framework for investigating merging operators for belief sets. This framework is a generalisation of our earlier work concerning consistency-based belief revision and...
James P. Delgrande, Torsten Schaub
ECCV
2004
Springer
16 years 8 months ago
Decision Theoretic Modeling of Human Facial Displays
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
Jesse Hoey, James J. Little
ECCV
2006
Springer
16 years 8 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady
ICML
2009
IEEE
16 years 7 months ago
Boosting with structural sparsity
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
John Duchi, Yoram Singer