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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Highly Cited

2014

Highly Cited

2014

- Richard Cole, Tim Roughgarden
- STOC
- 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

- Maria-Florina Balcan, Steve Hanneke, Jennifer Wortman Vaughan
- Machine Learning
- 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

- Pieter Abbeel, Daphne Koller, Andrew Y. Ng
- Journal of Machine Learning Research
- 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

- Sanjoy Dasgupta
- NIPS
- 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

- Shie Mannor, John N. Tsitsiklis
- Journal of Machine Learning Research
- 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

- Yi Li, Philip M. Long, Aravind Srinivasan
- SODA
- 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

- Peter L. Bartlett
- IEEE Trans. Information Theory
- 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

- Nir Friedman, Zohar Yakhini
- UAI
- 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

- Partha Niyogi, Federico Girosi
- Neural Computation
- 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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