AI RESEARCH
It does what it says on the tin: safe synthetic data from coarsened margins
arXiv CS.LG
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ArXi:2606.02101v1 Announce Type: cross This paper proposes a method of creating synthetic data (SD) that will have two important advantages for the user compared to other methods currently available. The first is transparency; unlike other methods, the person in receipt of the SD will know which of the relationships between variables in the original data will be approximately maintained in the SD. The second is a guarantee that the SD is derived from information that has already been judged to be free of disclosure risk.