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Inverse problems for structured datasets using parallel TAP equations and restricted Boltzmann machines.

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  • معلومة اضافية
    • المصدر:
      Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE
    • بيانات النشر:
      Original Publication: London : Nature Publishing Group, copyright 2011-
    • نبذة مختصرة :
      We propose an efficient algorithm to solve inverse problems in the presence of binary clustered datasets. We consider the paradigmatic Hopfield model in a teacher student scenario, where this situation is found in the retrieval phase. This problem has been widely analyzed through various methods such as mean-field approaches or the pseudo-likelihood optimization. Our approach is based on the estimation of the posterior using the Thouless-Anderson-Palmer (TAP) equations in a parallel updating scheme. Unlike other methods, it allows to retrieve the original patterns of the teacher dataset and thanks to the parallel update it can be applied to large system sizes. We tackle the same problem using a restricted Boltzmann machine (RBM) and discuss analogies and differences between our algorithm and RBM learning.
      (© 2021. The Author(s).)
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    • الموضوع:
      Date Created: 20211008 Latest Revision: 20240403
    • الموضوع:
      20240403
    • الرقم المعرف:
      PMC8497629
    • الرقم المعرف:
      10.1038/s41598-021-99353-2
    • الرقم المعرف:
      34620934