@inproceedings{628ac0de6aa14b1191d930767132d8cf,
title = "Finding galaxies in the shadows of quasars with Gaussian processes",
abstract = "We develop an automated technique for detecting damped Lyman-α absorbers (DLAs) along spectroscopic sightlines to quasi-stellar objects (QSOs or quasars). The detection of DLAs in large-scale spectroscopic surveys such as SDSS-III is critical to address outstanding cosmological questions, such as the nature of galaxy formation. We use nearly 50 000 QSO spectra to learn a tailored Gaussian process model for quasar emission spectra, which we apply to the DLA detection problem via Bayesian model selection. We demonstrate our method's effectiveness with a large-scale validation experiment on over 100 000 spectra, with excellent performance.",
author = "Roman Garnett and Shirley Ho and Jeff Schneider",
note = "Publisher Copyright: Copyright {\textcopyright} 2015 by the author(s).; 32nd International Conference on Machine Learning, ICML 2015 ; Conference date: 06-07-2015 Through 11-07-2015",
year = "2015",
language = "English",
series = "32nd International Conference on Machine Learning, ICML 2015",
publisher = "International Machine Learning Society (IMLS)",
pages = "1025--1033",
editor = "David Blei and Francis Bach",
booktitle = "32nd International Conference on Machine Learning, ICML 2015",
}