Fairness Constraints in High-Dimensional Generalized Linear Models
arXiv 2604.16610•5f270ec000d004e63446feaef3d77f7182460804df90aca426d48594df1a590b
Gibbs-posteriorItô-processesPAC-BayesPoisson-databatch-normalizationbetting-oddsblind-source-separationdimensionality-reductionefficient-market-hypothesisenergy-based-modelsfairnessfeature-extractiongeneralized-linear-modelsloss-spikesmachine learningodds-conversionoff-policy-evaluation (OPE)p-SNEprivacysensitive-attribute-inferencesingular-learning-theorystatistical-learning-theorytheorytime-seriestraining-instability
Paper metadata
- arXiv ID
- 2604.16610
- 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
- 5f270ec000d004e63446feaef3d77f7182460804df90aca426d48594df1a590b
- Enrichment time
- 2026-04-21T07:23:57Z
- AI-assisted enrichment
- Yes
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