Sample complexity

The sample complexity of a machine learning algorithm represents the number of training-samples that it needs in order to successfully learn a target… (More)
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Topic mentions per year

1988-2018
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Highly Cited
2014
Highly Cited
2014
In the design and analysis of revenue-maximizing auctions, auction performance is typically measured with respect to a prior… (More)
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Highly Cited
2008
Highly Cited
2008
We describe and explore a new perspective on the sample complexity of active learning. In many situations where it was generally… (More)
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Highly Cited
2006
Highly Cited
2006
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows… (More)
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Highly Cited
2005
Highly Cited
2005
We characterize the sample complexity of active learning problems in terms of a parameter which takes into account the specific… (More)
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Highly Cited
2003
Highly Cited
2003
  • Machandranath Kakade Gatsby
  • 2003
This thesis is a detailed investigation into the following question: how much data must an agent collect in order to perform… (More)
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Highly Cited
2003
Highly Cited
2003
We consider the multi-armed bandit problem under the PAC (“probably approximately correct”) model. It was shown by Even-Dar et al… (More)
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Highly Cited
2000
Highly Cited
2000
1 I n t r o d u c t i o n Many important applied problems can be modeled as learning from random examples. Examples include text… (More)
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Highly Cited
1998
Highly Cited
1998
Sample complexity results from computational learning theory, when applied to neural network learning for pattern classification… (More)
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Highly Cited
1996
Highly Cited
1996
In recent years there has been an increasing in­ terest in learning Bayesian networks from data. One of the most effective… (More)
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Highly Cited
1996
Highly Cited
1996
Feedforward networks together with their training algorithms are a class of regression techniques that can be used to learn to… (More)
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