@inproceedings{e9fdabe4a68d47979de7980141f11101,
title = "Predicting the outcomes of every process for which an asymptotically accurate stationary predictor exists is impossible",
abstract = "The problem of prediction consists in forecasting the conditional distribution of the next outcome given the past. Assume that the source generating the data is such that there is a stationary predictor whose error converges to zero (in a certain sense). The question is whether there is a universal predictor for all such sources, that is, a predictor whose error goes to zero if any of the sources that have this property is chosen to generate the data. This question is answered in the negative, contrasting a number of previously established positive results concerning related but smaller sets of processes.",
author = "Daniil Ryabko and Boris Ryabko",
year = "2015",
month = sep,
day = "28",
doi = "10.1109/ISIT.2015.7282646",
language = "English",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1204--1206",
booktitle = "Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015",
address = "United States",
note = "IEEE International Symposium on Information Theory, ISIT 2015 ; Conference date: 14-06-2015 Through 19-06-2015",
}