Learning from Collective Behavior
Abstract
Inspired by longstanding lines of research in sociology and related fields, and by more recent largepopulation human subject experiments on the In- ternet and the Web, we initiate a study of the computational issues in learning to model collective behavior from observed data. We define formal models for efficient learning in such settings, and provide both general theory and specific learning algorithms for these models.
Cite
Text
Kearns and Wortman. "Learning from Collective Behavior." Annual Conference on Computational Learning Theory, 2008.Markdown
[Kearns and Wortman. "Learning from Collective Behavior." Annual Conference on Computational Learning Theory, 2008.](https://mlanthology.org/colt/2008/kearns2008colt-learning/)BibTeX
@inproceedings{kearns2008colt-learning,
title = {{Learning from Collective Behavior}},
author = {Kearns, Michael J. and Wortman, Jennifer},
booktitle = {Annual Conference on Computational Learning Theory},
year = {2008},
pages = {99-110},
url = {https://mlanthology.org/colt/2008/kearns2008colt-learning/}
}