ML Anthology

Bayesian Multiple Instance Learning: Automatic Feature Selection and Inductive Transfer

Vikas C. Raykar, Balaji Krishnapuram, Jinbo Bi, Murat Dundar, R. Bharat Rao
ICML 2008 pp. 808-815
doi:10.1145/1390156.1390258 /icml/2008/raykar2008icml-bayesian/

Abstract

We propose a novel Bayesian multiple instance learning algorithm. This algorithm automatically identifies the relevant feature subset, and utilizes inductive transfer when learning multiple (conceptually related) classifiers. Experimental results indicate that the proposed baseline MIL method is more accurate than previous MIL algorithms and selects a much smaller set of useful features. Inductive transfer further improves the accuracy of the classifier as compared to learning each task individually.

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Cite

Text

Raykar et al. "Bayesian Multiple Instance Learning: Automatic Feature Selection and Inductive Transfer." International Conference on Machine Learning, 2008. doi:10.1145/1390156.1390258

Markdown

[Raykar et al. "Bayesian Multiple Instance Learning: Automatic Feature Selection and Inductive Transfer." International Conference on Machine Learning, 2008.](https://mlanthology.org/icml/2008/raykar2008icml-bayesian/) doi:10.1145/1390156.1390258

BibTeX

@inproceedings{raykar2008icml-bayesian,
  title     = {{Bayesian Multiple Instance Learning: Automatic Feature Selection and Inductive Transfer}},
  author    = {Raykar, Vikas C. and Krishnapuram, Balaji and Bi, Jinbo and Dundar, Murat and Rao, R. Bharat},
  booktitle = {International Conference on Machine Learning},
  year      = {2008},
  pages     = {808-815},
  doi       = {10.1145/1390156.1390258},
  url       = {https://mlanthology.org/icml/2008/raykar2008icml-bayesian/}
}