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Concentration and Confidence for Discrete Bayesian Sequence Predictors

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

Description

Keywords

Citation

URI

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

Collections

Open Access Research

Source

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

Type

Conference paper

Book Title

Entity type

Access Statement

License Rights

DOI

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

Restricted until

2037-12-31

Downloads

File
Description
01_Lattimore_Concentration_and_Confidence_2013.pdf (298.89 KB)

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