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Concentration and Confidence for Discrete Bayesian Sequence Predictors

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Date

2013

Authors

Lattimore, Tor
Hutter, Marcus
Sunehag, Peter

Journal Title

Journal ISSN

Volume Title

Publisher

Springer Berlin

Abstract

Bayesian sequence prediction is a simple technique for predicting future symbols sampled from an unknown measure on infinite sequences over a countable alphabet. While strong bounds on the expected cumulative error are known, there are only limited result

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Keywords

Citation

URI

http://hdl.handle.net/1885/65814

Collections

ANU Research Publications

Source

Algorithmic learning theory : 24th international conference, ALT 2013, Singapore, October 6-9 2013 : proceedings

Type

Conference paper

Book Title

Entity type

Access Statement

Open Access

License Rights

DOI

10.1007/978-3-642-40935-6_23

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01_Lattimore_Concentration_and_Confidence_2013.pdf (298.89 KB)

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