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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.
Cited literature [9 references]
https://hal.inria.fr/hal-01165876
Contributor : Daniil Ryabko <>
Submitted on : Wednesday, June 24, 2015 - 10:58:31 AM
Last modification on : Friday, March 22, 2019 - 1:34:52 AM
Document(s) archivé(s) le : Tuesday, April 25, 2017 - 6:24:06 PM
Contributor : Daniil Ryabko <>
Submitted on : Wednesday, June 24, 2015 - 10:58:31 AM
Last modification on : Friday, March 22, 2019 - 1:34:52 AM
Document(s) archivé(s) le : Tuesday, April 25, 2017 - 6:24:06 PM
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