Indefinitely oscillating martingales

Jan Leike*, Marcus Hutter

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    2 Citations (Scopus)

    Abstract

    We construct a class of nonnegative martingale processes that oscillate indefinitely with high probability. For these processes, we state a uniform rate of the number of oscillations for a given magnitude and show that this rate is asymptotically close to the theoretical upper bound. These bounds on probability and expectation of the number of upcrossings are compared to classical bounds from the martingale literature. We discuss two applications. First, our results imply that the limit of the minimum description length operator may not exist. Second, we give bounds on how often one can change one’s belief in a given hypothesis when observing a stream of data.

    Original languageEnglish
    Title of host publicationAlgorithmic Learning Theory - 25th International Conference, ALT 2014, Proceedings
    EditorsPeter Auer, Alexander Clark, Thomas Zeugmann, Sandra Zilles
    PublisherSpringer Verlag
    Pages321-335
    Number of pages15
    ISBN (Electronic)9783319116617
    DOIs
    Publication statusPublished - 2014
    Event25th International Conference on Algorithmic Learning Theory, ALT 2014 - Bled, Slovenia
    Duration: 8 Oct 201410 Oct 2014

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume8776
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference25th International Conference on Algorithmic Learning Theory, ALT 2014
    Country/TerritorySlovenia
    CityBled
    Period8/10/1410/10/14

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