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Predicting the outcomes of every process for which an asymptotically accurate stationary predictor exists is impossible. / Ryabko, Daniil; Ryabko, Boris.

Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1204-1206 7282646 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2015-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Ryabko, D & Ryabko, B 2015, Predicting the outcomes of every process for which an asymptotically accurate stationary predictor exists is impossible. in Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015., 7282646, IEEE International Symposium on Information Theory - Proceedings, vol. 2015-June, Institute of Electrical and Electronics Engineers Inc., pp. 1204-1206, IEEE International Symposium on Information Theory, ISIT 2015, Hong Kong, Hong Kong, 14.06.2015. https://doi.org/10.1109/ISIT.2015.7282646

APA

Ryabko, D., & Ryabko, B. (2015). Predicting the outcomes of every process for which an asymptotically accurate stationary predictor exists is impossible. In Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015 (pp. 1204-1206). [7282646] (IEEE International Symposium on Information Theory - Proceedings; Vol. 2015-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2015.7282646

Vancouver

Ryabko D, Ryabko B. Predicting the outcomes of every process for which an asymptotically accurate stationary predictor exists is impossible. In Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1204-1206. 7282646. (IEEE International Symposium on Information Theory - Proceedings). doi: 10.1109/ISIT.2015.7282646

Author

Ryabko, Daniil ; Ryabko, Boris. / Predicting the outcomes of every process for which an asymptotically accurate stationary predictor exists is impossible. Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1204-1206 (IEEE International Symposium on Information Theory - Proceedings).

BibTeX

@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",

}

RIS

TY - GEN

T1 - Predicting the outcomes of every process for which an asymptotically accurate stationary predictor exists is impossible

AU - Ryabko, Daniil

AU - Ryabko, Boris

PY - 2015/9/28

Y1 - 2015/9/28

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84969786555&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2015.7282646

DO - 10.1109/ISIT.2015.7282646

M3 - Conference contribution

AN - SCOPUS:84969786555

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 1204

EP - 1206

BT - Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE International Symposium on Information Theory, ISIT 2015

Y2 - 14 June 2015 through 19 June 2015

ER -

ID: 25331330