ML Anthology

Coarse Sample Complexity Bounds for Active Learning

Sanjoy Dasgupta
NeurIPS 2005 pp. 235-242
/neurips/2005/dasgupta2005neurips-coarse/

Abstract

We characterize the sample complexity of active learning problems in terms of a parameter which takes into account the distribution over the input space, the specific target hypothesis, and the desired accuracy.

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Cite

Text

Dasgupta. "Coarse Sample Complexity Bounds for Active Learning." Neural Information Processing Systems, 2005.

Markdown

[Dasgupta. "Coarse Sample Complexity Bounds for Active Learning." Neural Information Processing Systems, 2005.](https://mlanthology.org/neurips/2005/dasgupta2005neurips-coarse/)

BibTeX

@inproceedings{dasgupta2005neurips-coarse,
  title     = {{Coarse Sample Complexity Bounds for Active Learning}},
  author    = {Dasgupta, Sanjoy},
  booktitle = {Neural Information Processing Systems},
  year      = {2005},
  pages     = {235-242},
  url       = {https://mlanthology.org/neurips/2005/dasgupta2005neurips-coarse/}
}