@inproceedings{89f5d7f065e24a43ab36f9e6bcc9a6e6,
title = "Bargaining Compatible Explanations",
abstract = "Within the framework of ensemble methods, we investigate on a compatible learning scheme, denoted as learning by gossip with the aim of assessing its feasibility when facing a rather complex target function. Compatibility is in terms of probability that the learned function could be actually at the basis of the observed training set, hence an explanation of it. Feasibility is in terms of the related MSE on test sets. We base or conclusions on both theoretical and numerical arguments that are tossed on a well known benchmark.",
keywords = "Compatible-explanation, Ensemble-learning, Learning-by-gossip, Subsymbolic-kernels",
author = "Bruno Apolloni and {Al Shehhi}, Aamna and Ernesto Damiani",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 4th IEEE International Conference on Cognitive Computing, ICCC 2019 ; Conference date: 08-07-2019 Through 13-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ICCC.2019.00028",
language = "British English",
series = "Proceedings - 2019 IEEE International Conference on Cognitive Computing, ICCC 2019 - Part of the 2019 IEEE World Congress on Services",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "98--105",
editor = "Elisa Bertino and Chang, {Carl K.} and Peter Chen and Ernesto Damiani and Michael Goul and Katsunori Oyama",
booktitle = "Proceedings - 2019 IEEE International Conference on Cognitive Computing, ICCC 2019 - Part of the 2019 IEEE World Congress on Services",
address = "United States",
}