@inproceedings{d0d02f8302534e69b4e1de5b65fb8a93,
title = "Regression to a linear lower bound with outliers: An exponentially modified Gaussian noise model",
abstract = "A regression method to estimate a linear bound in the presence of outliers is discussed. An exponentially-modified Gaussian (EMG) noise model is proposed, based on a maximum entropy argument. The resulting {\textquotedblleft}EMG regression{\textquotedblright} method is shown to encompass the classical linear regression (with Gaussian noise) and a minimum regression (with exponential noise) as special cases. Simulations are performed to assess the consistency of the regression as well as its resilience to model mismatch. We conclude with an example taken from a real-world study of human performance in rapid aiming with application to human-computer interaction.",
author = "Julien Gori and Olivier Rioul",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE; 27th European Signal Processing Conference, EUSIPCO 2019 ; Conference date: 02-09-2019 Through 06-09-2019",
year = "2019",
month = sep,
day = "1",
doi = "10.23919/EUSIPCO.2019.8902946",
language = "English",
series = "European Signal Processing Conference",
publisher = "European Signal Processing Conference, EUSIPCO",
booktitle = "EUSIPCO 2019 - 27th European Signal Processing Conference",
}