@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",

}