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CVPR
2008
IEEE
14 years 9 months ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
IJCAI
1989
13 years 8 months ago
Utilization Filtering: A Method for Reducing the Inherent Harmfulness of Deductively Learned Knowledge
This paper highlights a phenomenon that causes deductively learned knowledge to be harmful when used for problem solving. The problem occurs when deductive problem solvers encount...
Shaul Markovitch, Paul D. Scott
ATAL
2010
Springer
13 years 8 months ago
Learning context conditions for BDI plan selection
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
Dhirendra Singh, Sebastian Sardiña, Lin Pad...
JMLR
2010
129views more  JMLR 2010»
13 years 2 months ago
Learning Polyhedral Classifiers Using Logistic Function
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
Naresh Manwani, P. S. Sastry
ICML
2004
IEEE
14 years 1 months ago
Ensembles of nested dichotomies for multi-class problems
Nested dichotomies are a standard statistical technique for tackling certain polytomous classification problems with logistic regression. They can be represented as binary trees ...
Eibe Frank, Stefan Kramer