Applications of concentration inequalities for statistical scoring and ranking problems
ESAIM. Proceedings, Tome 44 (2014), pp. 99-109
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In this overview paper, we consider the scoring approach applied to the ranking problem from a nonparametric perspective. We first focus on the problem of ROC curve optimization in terms of description of optimal elements. Then, we introduce summaries of this function-valued description of performance which are related to well-known statistics that are of higher order compared to averages of i.i.d. random variables. Eventually, we consider consistency and fast convergence results that rely on applications of concentration inequalities which involve U- and R-processes. This is a joint work with Stéphan Clémençon, Marine Depecker, Gábor Lugosi, and Sylvain Robbiano.
@article{EP_2014_44_a5,
author = {Nicolas Vayatis},
title = {Applications of concentration inequalities for statistical scoring and ranking problems},
journal = {ESAIM. Proceedings},
pages = {99--109},
year = {2014},
volume = {44},
doi = {10.1051/proc/201444005},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.1051/proc/201444005/}
}
TY - JOUR AU - Nicolas Vayatis TI - Applications of concentration inequalities for statistical scoring and ranking problems JO - ESAIM. Proceedings PY - 2014 SP - 99 EP - 109 VL - 44 UR - http://geodesic.mathdoc.fr/articles/10.1051/proc/201444005/ DO - 10.1051/proc/201444005 LA - en ID - EP_2014_44_a5 ER -
Nicolas Vayatis. Applications of concentration inequalities for statistical scoring and ranking problems. ESAIM. Proceedings, Tome 44 (2014), pp. 99-109. doi: 10.1051/proc/201444005
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