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spectral_scheduling.md

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Spectral Scheduling

labels: experimental

  1. learn a singular basis over the data
  2. treat the eigenvalues as relative sampling weight, sample a basis dimension/component each batch
  3. sample a batch of data, using that datum's value in the sampled component as their relative likelihood (threshold this)
  4. incorporate a temperature term so we can sample disproportionately from the important components in early training, progressively increasing the weight of the tail probabilities.

can we learn this online?