NeurIPS 2015poster24 citations
Evaluating the statistical significance of biclusters
Jason Lee, Yuekai Sun, Jonathan E Taylor
Abstract
Biclustering (also known as submatrix localization) is a problem of high practical relevance in exploratory analysis of high-dimensional data. We develop a framework for performing statistical inference on biclusters found by score-based algorithms. Since the bicluster was selected in a data dependent manner by a biclustering or localization algorithm, this is a form of selective inference. Our framework gives exact (non-asymptotic) confidence intervals and p-values for the significance of the selected biclusters. Further, we generalize our approach to obtain exact inference for Gaussian statistics.
BibTeX
@inproceedings{NIPS2015_4558dbb6,
author = {Lee, Jason D and Sun, Yuekai and Taylor, Jonathan E},
booktitle = {Advances in Neural Information Processing Systems},
editor = {C. Cortes and N. Lawrence and D. Lee and M. Sugiyama and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Evaluating the statistical significance of biclusters},
url = {https://proceedings.neurips.cc/paper_files/paper/2015/file/4558dbb6f6f8bb2e16d03b85bde76e2c-Paper.pdf},
volume = {28},
year = {2015}
}