Design-Based Supervised Learning with Noisy Human Labels
arXiv 2607.15455•a88879d9e12f4b53ee2528d050e37b53449ae526de6f7cafaea1f6a2e1ec9ce7
adversarial-robustnessauditabilitybioinformaticsbiosecuritydata-privacydataset-poisoningdiffusion-modelsgenerative-modelshealthcare-operationslabel-noisemachine-learningmodel-robustnessperformativityretraining-feedback-loopssynthetic-datatime-series-data
Paper metadata
- arXiv ID
- 2607.15455
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- a88879d9e12f4b53ee2528d050e37b53449ae526de6f7cafaea1f6a2e1ec9ce7
- Enrichment time
- 2026-07-20T07:24:00Z
- AI-assisted enrichment
- Yes
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