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Adaptive Exact Learning in a Mixed-Up World: Dealing with Periodicity, Errors and Jumbled-Index Queries in String Reconstruction

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String Processing and Information Retrieval (SPIRE 2020)

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Abstract

We study the query complexity of exactly reconstructing a string from adaptive queries, such as substring, subsequence, and jumbled-index queries. Such problems have applications, e.g., in computational biology. We provide a number of new and improved bounds for exact string reconstruction for settings where either the string or the queries are “mixed-up”.

The full version of this paper is available in [5].

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Notes

  1. 1.

    Our algorithms assume that S is periodic (\(k>1\)), while the Periodicity Lemma (1) only requires a string to have a period (\(k>0\)).

  2. 2.

    A more sophisticated version of this procedure exists (see [17]) that actually improves the constant in the time complexity, but for simplicity, we use the traditional algorithm, which is asymptotically equivalent.

  3. 3.

    Pseudo-code can be found in the full version of the paper [5], where the number of queries is also shown for each step involving queries.

  4. 4.

    Pseudo-code can be found in the full version of the paper [5], where the number of queries is also shown for each step involving queries.

  5. 5.

    Pseudo-code can be found in the full version of the paper [5], where the number of queries is also shown for each step involving queries.

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Acknowledgments

This research was funded in part by the U.S. National Science Foundation under grant 1815073. Amihood Amir was partly supported by BSF grant 2018141 and ISF grant 1475-18.

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Authors and Affiliations

  1. Department of Computer Science, University of California Irvine, Irvine, USA

    Ramtin Afshar, Michael T. Goodrich & Pedro Matias

  2. Department of Computer Science, Bar Ilan University, Ramat Gan, Israel

    Amihood Amir

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  1. Ramtin Afshar
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Correspondence to Pedro Matias .

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  1. CISE Department, University of Florida, Gainesville, FL, USA

    Christina Boucher

  2. Department of Computer Science, University of Central Florida, Orlando, FL, USA

    Sharma V. Thankachan

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Afshar, R., Amir, A., Goodrich, M.T., Matias, P. (2020). Adaptive Exact Learning in a Mixed-Up World: Dealing with Periodicity, Errors and Jumbled-Index Queries in String Reconstruction. In: Boucher, C., Thankachan, S.V. (eds) String Processing and Information Retrieval. SPIRE 2020. Lecture Notes in Computer Science(), vol 12303. Springer, Cham. https://doi.org/10.1007/978-3-030-59212-7_12

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  • DOI: https://doi.org/10.1007/978-3-030-59212-7_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59211-0

  • Online ISBN: 978-3-030-59212-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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