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Lightweight Adaptive Balancer (LUA version)

Given

  • a total evaluation budget N
  • an initial budget N0
  • a pruning factor of P,

this would explore (say) 10,000 unlabelled items as follows:

  1. use N0 evalaution to label four items ;
  2. divide labelled items into best and rest using a multi-goal criteria;
  3. build a classifier to find, for unlabelled item, B=like(best), R=like(resti);
  4. sort, in ascending order, the remaining 9996 items by -B/R;
  5. label the top item (so N=N-1), and
  6. discard the last P% unlabelled items;
  7. update best and rest with this new item;
  8. if N > 0, loop back to (2)
    • Else terminate, returning the top item in best.

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LAB = lean adaptive brain (via sequential model optimization)

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