Application · Trajectory matching
Dataset Distillation for Medical Dataset Sharing
Guang Li, Ren Togo, Takahiro Ogawa, Miki Haseyama
AAAI 2023 Workshop · first public 2023-01-01
In one paragraph
Applies trajectory-matching dataset distillation (the linked code builds on MTT) to a medical imaging dataset to produce a small, shareable synthetic set for cross-institution medical data sharing, following the same authors' prior soft-label distillation work on gastric X-ray images.
Where it sits
- Trajectory matching (Surrogate matching)
- Setting: Image classification
BibTeX (generated; prefer the venue's official entry)
@article{li2023dataset,
title = {Dataset Distillation for Medical Dataset Sharing},
author = {Guang Li and Ren Togo and Takahiro Ogawa and Miki Haseyama},
journal = {AAAI 2023 Workshop},
year = {2023}
}Nearby in Trajectory matching
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AMD — Asynchronous Matching with Dynamic Sampling for Multimodal Dataset Distillation
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RepBlend — Beyond Modality Collapse: Representations Blending for Multimodal Dataset Distillation
Xin Zhang, Ziruo Zhang, Jiawei Du et al. · NeurIPS 2025notableVision–languagepaper ↗
MKDT — Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks
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