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» Hypothesis Spaces for Learning
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98
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COLT
1993
Springer
15 years 6 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
115
Voted
COLT
1998
Springer
15 years 6 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
15 years 3 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. ...
110
Voted
SAINT
2005
IEEE
15 years 7 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...
102
Voted
COGSCI
2007
87views more  COGSCI 2007»
15 years 1 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