Conformal Risk Minimization for Semi-Supervised Domain Adaptation via Optimal Transport
Ranking
Overall
78
Content
95
Popularity
37
Observed public metrics from 1 member.
Merged summary
TL;DR - This paper integrates conformal risk minimization into semi-supervised domain adaptation, using optimal-transport pseudolabels to compensate for scarce labeled target-domain data. The approach aims to produce clinically useful prediction sets that remain coverage-valid and compact under patient-population shifts.
- Jointly optimizes domain invariance, predictive performance, and conformal-set efficiency rather than applying conformal prediction post hoc.
- Uses optimal transport to pseudolabel unlabeled target examples, supplying the training signal needed to estimate nonconformity thresholds with few target labels.
- Targets compact, distribution-free prediction sets while preserving formal coverage guarantees.
- Supports domain-specific constraints, such as excluding mutually contradictory diagnoses in skin-lesion classification.
Sources (1)
Conformal Risk Minimization for Semi-Supervised Domain Adaptation via Optimal Transport
Public signals
Semantic Scholar citations 0 · Semantic Scholar influential citations 0
TL;DR - This paper integrates conformal risk minimization into semi-supervised domain adaptation, using optimal-transport pseudolabels to compensate for scarce labeled target-domain data. The approach aims to produce clinically useful prediction sets that remain coverage-valid and compact under patient-population shifts.
- Jointly optimizes domain invariance, predictive performance, and conformal-set efficiency rather than applying conformal prediction post hoc.
- Uses optimal transport to pseudolabel unlabeled target examples, supplying the training signal needed to estimate nonconformity thresholds with few target labels.
- Targets compact, distribution-free prediction sets while preserving formal coverage guarantees.
- Supports domain-specific constraints, such as excluding mutually contradictory diagnoses in skin-lesion classification.