Pseudo-Labeling for Unsupervised Domain Adaptation with Kernel GLMs
arXiv 2603.19422•c1447e61c87656e7c94d0eeabcb4b5f85c823a6ad0ac8e1a4eb8001bcccedec8
2026Q-learningarXivclusteringdata-leakagediffusion-modelsdomain-adaptationdynamic-graphsdynamic-treatment-regimesensemble-methods','bagging'explainabilityfinite-context-modelsgaussian-mixture-modelsgenerative-modelsgeophysical-inversiongraphshyperparameter-selectionkernel-GLMmachine-learningmemorizationmodel-selectionprivacypseudo-labelingreinforcement-learningspectral-embedding
Paper metadata
- arXiv ID
- 2603.19422
- 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
- c1447e61c87656e7c94d0eeabcb4b5f85c823a6ad0ac8e1a4eb8001bcccedec8
- Enrichment time
- 2026-03-23T07:23:56Z
- AI-assisted enrichment
- Yes
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