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Bridging the Gap from Asymmetry Tricks to Decorrelation Principles in Non-contrastive Self-supervised Learning A Proof of Lemma 3.2

Neural Information Processing Systems

We can expand the loss (4), i.e., Table 5 shows more results of our method with different configurations and hyperparameter settings.

  lemma 3, non-contrastive self-supervised, stopgrad, (11 more...)
  Technology: Information Technology > Artificial Intelligence > Machine Learning > Inductive Learning (0.41)

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Bridging the Gap from Asymmetry Tricks to Decorrelation Principles in Non-contrastive Self-supervised Learning A Proof of Lemma 3.2

Neural Information Processing Systems

We can expand the loss (4), i.e., Table 5 shows more results of our method with different configurations and hyperparameter settings.

  lemma 3, non-contrastive self-supervised, stopgrad, (11 more...)
  Technology: Information Technology > Artificial Intelligence > Machine Learning > Inductive Learning (0.41)

Add feedback