NeurIPS 2016poster24 citations
Fast recovery from a union of subspaces
Chinmay Hegde, Piotr Indyk, Ludwig Schmidt
Abstract
We address the problem of recovering a high-dimensional but structured vector from linear observations in a general setting where the vector can come from an arbitrary union of subspaces. This setup includes well-studied problems such as compressive sensing and low-rank matrix recovery. We show how to design more efficient algorithms for the union-of subspace recovery problem by using
BibTeX
@inproceedings{NIPS2016_8929c70f,
author = {Hegde, Chinmay and Indyk, Piotr and Schmidt, Ludwig},
booktitle = {Advances in Neural Information Processing Systems},
editor = {D. Lee and M. Sugiyama and U. Luxburg and I. Guyon and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Fast recovery from a union of subspaces},
url = {https://proceedings.neurips.cc/paper_files/paper/2016/file/8929c70f8d710e412d38da624b21c3c8-Paper.pdf},
volume = {29},
year = {2016}
}