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» Learning Hierarchical Shape Models from Examples
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IJCAI
2007
13 years 11 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
ALT
2005
Springer
14 years 7 months ago
PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance
We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
Nick Palmer, Paul W. Goldberg
CVBIA
2005
Springer
14 years 3 months ago
Analyzing Anatomical Structures: Leveraging Multiple Sources of Knowledge
Analysis of medical images, especially the extraction of anatomical structures, is a critical component of many medical applications: surgical planning and navigation, and populati...
W. Eric L. Grimson, Polina Golland
CVPR
2003
IEEE
15 years 4 days ago
What is the Space of Camera Response Functions?
Many vision applications require precise measurement of scene radiance. The function relating scene radiance to image brightness is called the camera response. We analyze the prop...
Michael D. Grossberg, Shree K. Nayar
MST
2000
86views more  MST 2000»
13 years 10 months ago
Team Learning of Computable Languages
A team of learning machines is a multiset of learning machines. A team is said to successfully learn a concept just in case each member of some nonempty subset, of predetermined s...
Sanjay Jain, Arun Sharma