Reconstructing point sets from distance distributions

HIGHLIGHTS

  • who: Distributions and collaborators from the (UNIVERSITY) have published the Article: Reconstructing Point Sets From Distance Distributions, in the Journal: (JOURNAL)
  • what: The authors show how the distance distribution is then simply a collection of quadratic functionals of this density and propose to recover the point locations so that the estimated distance distribution matches the measured distance distribution. The authors propose to relax the integer program to a constrained nonconvex optimization problem that can be solved efficiently using projected gradient descent with a spectral initializer. In the following the authors discuss how to extract the . . .

     

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