Method · Decoupled teacher-driven synthesis

Information Compensation: A Fix for Any-scale Dataset Distillation

Peng Sun

ICLR 2024 Workshop · first public 2024-01

paper ↗catalogued✓ metadata verified

In one paragraph

Addresses information loss that arises when decoupled ('squeeze-recover-relabel' style) dataset distillation is applied across different compression scales or budgets. Method details could not be independently verified: OpenReview returned only a browser-verification challenge, and no alternative fetchable copy of the abstract was found.

Where it sits

Decoupled teacher-driven synthesis (Decoupled synthesis)
Setting: Image classification

BibTeX (generated; prefer the venue's official entry)

@article{sun2024information,
  title   = {Information Compensation: A Fix for Any-scale Dataset Distillation},
  author  = {Peng Sun},
  journal = {ICLR 2024 Workshop},
  year    = {2024}
}

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