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» Probably Approximately Correct Learning
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109
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ECAI
2004
Springer
15 years 6 months ago
Instance-Based Prediction with Guaranteed Confidence
Instance-based learning (IBL) algorithms have proved to be successful in many applications. However, as opposed to standard statistical methods, a prediction in IBL is usually give...
Eyke Hüllermeier
153
Voted
DAGM
2008
Springer
15 years 4 months ago
Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification
Three-dimensional electron-microscopic image stacks with almost isotropic resolution allow, for the first time, to determine the complete connection matrix of parts of the brain. I...
Björn Andres, Ullrich Köthe, Moritz Helm...
105
Voted
FOCS
2009
IEEE
15 years 9 months ago
Agnostic Learning of Monomials by Halfspaces Is Hard
— We prove the following strong hardness result for learning: Given a distribution on labeled examples from the hypercube such that there exists a monomial (or conjunction) consi...
Vitaly Feldman, Venkatesan Guruswami, Prasad Ragha...
139
Voted
WSC
2007
15 years 5 months ago
New greedy myopic and existing asymptotic sequential selection procedures: preliminary empirical results
Statistical selection procedures can identify the best of a finite set of alternatives, where “best” is defined in terms of the unknown expected value of each alternative’...
Stephen E. Chick, Jürgen Branke, Christian Sc...
119
Voted
IJAR
2010
105views more  IJAR 2010»
14 years 12 months ago
A tree augmented classifier based on Extreme Imprecise Dirichlet Model
In this paper we present TANC, i.e., a tree-augmented naive credal classifier based on imprecise probabilities; it models prior near-ignorance via the Extreme Imprecise Dirichlet ...
G. Corani, C. P. de Campos