On Bisubmodular Maximization
Abstract
Bisubmodularity extends the concept of submodularity to set functions with two arguments. We show how bisubmodular maximization leads to richer value-of-information problems, using examples in sensor placement and feature selection. We present the first constant-factor approximation algorithm for a wide class of bisubmodular maximizations.
Cite
Text
Singh et al. "On Bisubmodular Maximization." Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012.Markdown
[Singh et al. "On Bisubmodular Maximization." Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012.](https://mlanthology.org/aistats/2012/singh2012aistats-bisubmodular/)BibTeX
@inproceedings{singh2012aistats-bisubmodular,
title = {{On Bisubmodular Maximization}},
author = {Singh, Ajit and Guillory, Andrew and Bilmes, Jeff},
booktitle = {Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics},
year = {2012},
pages = {1055-1063},
volume = {22},
url = {https://mlanthology.org/aistats/2012/singh2012aistats-bisubmodular/}
}