ICML-Practical and Private (Deep) Learning Without Sampling or Shuffling

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Practical and Private (Deep) Learning Without Sampling or Shuffling

  Peter Kairouz 1 Brendan McMahan 1 Shuang Song 1 Om Thakkar 1 Abhradeep Thakurta 1 Zheng Xu 1

             Abstract                  in the context of distributed settings like federated learn-
                                   ing (FL) where one has little control on which subset of
   We consider training models with differential          the training data one sees at any time (Kairouz et al., 2019;
   privacy (DP) using m ...

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关键词：Practical Sampling Learning earning practic