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On Recovering Latent Factors From Sampling And Firing Graph

Machine Learning 2019-09-23 v1 Machine Learning

Abstract

Consider a set of latent factors whose observable effect of activation is caught on a measure space that appears as a grid of bits tacking value in {0,1}\{0, 1 \}. This paper intend to deliver a theoretical and practical answer to the question: Given that we have access to a perfect indicator of the activation of latent factors that label a finite dataset of grid's activity, can we imagine a procedure to build a generic identificator of factor's activations ?

Keywords

Cite

@article{arxiv.1909.09493,
  title  = {On Recovering Latent Factors From Sampling And Firing Graph},
  author = {Pierre Gouedard},
  journal= {arXiv preprint arXiv:1909.09493},
  year   = {2019}
}

Comments

38 pages, 9 figures, 1 table