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BioGD: Bio-inspired robust gradient descent

  • Published:2019-07-05 Issue:7 Volume:14 Page:e0219004
  • ISSN:1932-6203
  • Container-title:PLOS ONE
  • language:en
  • Short-container-title:PLoS ONE

Author:

Kulikovskikh IlonaORCID,Prokhorov Sergej,Lipić TomislavORCID,Legović Tarzan,Šmuc Tomislav

Funder

Ministry of Science and Higher Education of the Russian Federation

Ministry of Education and Science of the Russian Federation

Russian Foundation for Basic Research

Croatian Government and the European Union through the European Regional Development Fund

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Performance Improvement of Logistic Regression for Binary Classification by Gauss-Newton Method;2022 5th International Conference on Mathematics and Statistics;2022-06-17

2. The criterion power for identifying symmetric models;IOP Conference Series: Materials Science and Engineering;2020-05-01

3. Reducing computational costs in deep learning on almost linearly separable training data;Computer Optics;2020-04
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