180 search results - page 7 / 36 » Improved bounds on the sample complexity of learning |
120
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COLT
2000
Springer
15 years 4 months ago
2000
Springer
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
96
Voted
JMLR
2006
14 years 11 months ago
2006
Fast and frugal heuristics are well studied models of bounded rationality. Psychological research has proposed the take-the-best heuristic as a successful strategy in decision mak...
121
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ALT
2010
Springer
14 years 11 months ago
2010
Springer
This paper is concerned with the combinatorial structure of concept classes that can be learned from a small number of examples. We show that the recently introduced notion of recu...
ICML
2008
IEEE
16 years 13 days ago
2008
IEEE
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
72
Voted
CORR
2010
Springer
14 years 11 months ago
2010
Springer
We derive generalization bounds for learning algorithms based on their robustness: the property that if a testing sample is "similar" to a training sample, then the test...