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The Linear Estimation Problem and Information in Big-Data Systems

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Abstract

This paper addresses the problem of transforming the optimal linear estimation procedure in such a way that separate fragments of initial data are processed individually and concurrently. A representation of intermediate information is proposed that allows an algorithm to concurrently extract this information from each initial data set, combine it, and use it for estimation. It is shown that, on an information space constructed, an ordering is induced that reflects the concept of information quality.

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Author information

Authors and Affiliations

  1. Lomonosov Moscow State University, Moscow, 119991, Russia

    P. V. Golubtsov

  2. National Research University Higher School of Economics, Moscow, 101000, Russia

    P. V. Golubtsov

Authors
  1. P. V. Golubtsov
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Correspondence to P. V. Golubtsov.

Additional information

Original Russian Text © P.V. Golubtsov, 2018, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2: Informatsionnye Protsessy i Sistemy, 2018, No. 3, pp. 23–30.

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Golubtsov, P.V. The Linear Estimation Problem and Information in Big-Data Systems. Autom. Doc. Math. Linguist. 52, 73–79 (2018). https://doi.org/10.3103/S0005105518020024

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  • DOI: https://doi.org/10.3103/S0005105518020024

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