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Faster Algorithms for Estimating the Mean of a Quadratic Expression Under Uncertainty

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Fuzzy Information Processing 2023 (NAFIPS 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 751))

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Abstract

In many practical situations, we can safely approximate the actual nonlinear dependence by a quadratic expression. For such situations, there exist techniques for estimating the uncertainty of the result of data processing based on the known information about the uncertainty of the input data – for example, for estimating the mean value of the corresponding approximation error. However, many such techniques are somewhat time-consuming. In this paper, we propose faster algorithms for solving this problem.

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Acknowledgment

This work was supported in part by the National Science Foundation grants 1623190 (A Model of Change for Preparing a New Generation for Professional Practice in Computer Science), HRD-1834620 and HRD-2034030 (CAHSI Includes), and by the AT &T Fellowship in Information Technology.

It was also supported by the program of the development of the Scientific-Educational Mathematical Center of Volga Federal District No. 075-02-2020-1478, and by a grant from the Hungarian National Research, Development and Innovation Office (NRDI).

The authors are thankful to the anonymous referees for valuable suggestions.

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, 500 W. University, El Paso, TX, 79968, USA

    Martine Ceberio & Vladik Kreinovich

  2. Department of Teacher Education, University of Texas at El Paso, 500 W. University, El Paso, TX, 79968, USA

    Olga Kosheleva

  3. Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, 11794, USA

    Lev Ginzburg

Authors
  1. Martine Ceberio
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  2. Vladik Kreinovich
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  3. Olga Kosheleva
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  4. Lev Ginzburg
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Corresponding author

Correspondence to Vladik Kreinovich .

Editor information

Editors and Affiliations

  1. University of Cincinnati, Cincinnati, OH, USA

    Kelly Cohen

  2. Thales Avionics, Cincinnati, OH, USA

    Nicholas Ernest

  3. DigiPen Institute of Technology, Redmond, WA, USA

    Barnabas Bede

  4. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Ceberio, M., Kreinovich, V., Kosheleva, O., Ginzburg, L. (2023). Faster Algorithms for Estimating the Mean of a Quadratic Expression Under Uncertainty. In: Cohen, K., Ernest, N., Bede, B., Kreinovich, V. (eds) Fuzzy Information Processing 2023. NAFIPS 2023. Lecture Notes in Networks and Systems, vol 751. Springer, Cham. https://doi.org/10.1007/978-3-031-46778-3_27

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