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CVIU
2008
188views more  CVIU 2008»
13 years 7 months ago
Learning function-based object classification from 3D imagery
We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical ...
Michael Pechuk, Octavian Soldea, Ehud Rivlin
CIKM
1997
Springer
13 years 11 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
NIPS
1998
13 years 8 months ago
Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
This paper presents probabilistic modeling methods to solve the problem of discriminating between five facial orientations with very little labeled data. Three models are explored...
Shumeet Baluja
CVPR
2000
IEEE
14 years 9 months ago
Learning from One Example through Shared Densities on Transforms
We define a process called congealing in which elements of a dataset (images) are brought into correspondence with each other jointly, producing a data-defined model. It is based ...
Erik G. Miller, Nicholas E. Matsakis, Paul A. Viol...
EDM
2009
116views Data Mining» more  EDM 2009»
13 years 5 months ago
Determining the Significance of Item Order In Randomized Problem Sets
Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collecte...
Zachary A. Pardos, Neil T. Heffernan