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I have read an article talking about binary clustering using Matrix factorization(see attached), but i would like to understand some optimization concepts:

  • Is it reasonable to use a Frobenius norm in such optimization?
  • What does it mean the centroid constraint: C^T*1=0, and why it is equivalent to K-means especially in this case (When rho is large)?
  • Is there other constraints that could improve clustering optimization?
  • Is there other optimization technique in place of DPLM(Discrete Proximal Linearized Minimization)?

Binary data clustering by Matrix factorization

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  • $\begingroup$ Hi. I just want to let you know that you cause use latex on this site. $\endgroup$ – nbro Aug 18 '20 at 0:11
  • $\begingroup$ Could you link the whole article? $\endgroup$ – Tinu Aug 18 '20 at 7:40
  • $\begingroup$ semanticscholar.org/paper/… $\endgroup$ – user40370 Aug 18 '20 at 17:05

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