Design-Based Supervised Learning with Noisy Human Labels
2026-07-20T07:24:00Z•a88879d9e12f4b53ee2528d050e37b53449ae526de6f7cafaea1f6a2e1ec9ce7
adversarial-robustnessauditabilitybioinformaticsbiosecuritydata-privacydataset-poisoningdiffusion-modelsgenerative-modelshealthcare-operationslabel-noisemachine-learningmodel-robustnessperformativityretraining-feedback-loopssynthetic-datatime-series-data
What happened
This feed contains a set of July 2026 ML/statistics papers addressing label-noise correction (PA-DSL), performativity and retraining stability, interpretable hyperparameter sensitivity, probabilistic and sequence-based methods for gene regulatory network (GRN) inference, cluster-aware optimal transport, proactive bed-request policies for emergency departments, prediction-only distillation, diffusion-model sensitivity to mixture weights, theory of binary iterative hard thresholding for 1-bit compressed sensing, and evaluation of synthetic sequential tabular data for time-awareness. Security-rep
Why it matters
A reviewed impact interpretation has not been published for this record.
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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