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Penalty-Based Data Aggregation in Real Normed Vector Spaces

  • Lucian CoroianuEmail author
  • Marek Gagolewski
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 981)

Abstract

The problem of penalty-based data aggregation in generic real normed vector spaces is studied. Some existence and uniqueness results are indicated. Moreover, various properties of the aggregation functions are considered.

Keywords

Penalty-based aggregation Prototype learning Means averages and medians Vector spaces Fermat–Weber problem 

Notes

Acknowledgments

The contribution of L. Coroianu was supported by a grant of Ministry of Research and Innovation, CNCS-UEFISCDI, project number PN-III-P1-1.1-PD-2016-1416, within PNCDI III. M. Gagolewski acknowledges the support by the Czech Science Foundation through the project No. 18-06915S.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Mathematics and InformaticsUniversity of OradeaOradeaRomania
  2. 2.Faculty of Mathematics and Information ScienceWarsaw University of TechnologyWarsawPoland
  3. 3.Systems Research InstitutePolish Academy of SciencesWarsawPoland

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