The paper proposes that noise injected into high-level data features before decoding regularizes hidden layers like Tikhonov or Dropout, but the claim is only an analogy, not a demonstrated result.
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On Regularization Properties of Artificial Datasets for Deep Learning
The paper proposes that noise injected into high-level data features before decoding regularizes hidden layers like Tikhonov or Dropout, but the claim is only an analogy, not a demonstrated result.