Machine Teaching: An Inverse Problem to Machine Learning and an Approach Toward Optimal Education

AAAI 2015 pp. 4083-4087

doi:10.1609/AAAI.V29I1.9761 /aaai/2015/zhu2015aaai-machine/

Abstract

I draw the reader's attention to machine teaching, the problem of finding an optimal training set given a machine learning algorithm and a target model. In addition to generating fascinating mathematical questions for computer scientists to ponder, machine teaching holds the promise of enhancing education and personnel training. The Socratic dialogue style aims to stimulate critical thinking.

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Text

Zhu. "Machine Teaching: An Inverse Problem to Machine Learning and an Approach Toward Optimal Education." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9761

Markdown

[Zhu. "Machine Teaching: An Inverse Problem to Machine Learning and an Approach Toward Optimal Education." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/zhu2015aaai-machine/) doi:10.1609/AAAI.V29I1.9761

BibTeX

@inproceedings{zhu2015aaai-machine,
  title     = {{Machine Teaching: An Inverse Problem to Machine Learning and an Approach Toward Optimal Education}},
  author    = {Zhu, Xiaojin},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {4083-4087},
  doi       = {10.1609/AAAI.V29I1.9761},
  url       = {https://mlanthology.org/aaai/2015/zhu2015aaai-machine/}
}