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» Hypothesis Spaces for Learning
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COLT
1993
Springer
14 years 1 months ago
Learning from a Population of Hypotheses
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
Michael J. Kearns, H. Sebastian Seung
COLT
1998
Springer
14 years 1 months ago
Self Bounding Learning Algorithms
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
Yoav Freund
BMVC
1998
13 years 11 months ago
Learning Enhanced 3D Models for Vehicle Tracking
This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic obj...
James M. Ferryman, Anthony D. Worrall, Stephen J. ...
SAINT
2005
IEEE
14 years 3 months ago
Inductive Logic Programming for Structure-Activity Relationship Studies on Large Scale Data
Inductive Logic Programming (ILP) is a combination of inductive learning and first-order logic aiming to learn first-order hypotheses from training examples. ILP has a serious b...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...
COGSCI
2007
87views more  COGSCI 2007»
13 years 9 months ago
Explaining Color Term Typology With an Evolutionary Model
An expression-induction model was used to simulate the evolution of basic color terms to test Berlin and Kay’s (1969) hypothesis that the typological patterns observed in basic ...
Mike Dowman