Online Survival Analysis: A Bandit Approach under Cox PH Model
arXiv 2604.20296•7135ddeb0bf64d89f5a07f35fe0aaa4d8021f0ec9a3eaef5a57adfc53f1d5c2b
Cox-PHERM-RERFisher-RaoGibbs-measuresLangevinRenyi-DPRicci-curvatureRiemannian-manifoldsWassersteinarxivbanditscausal-inference','symbolic-computation','Gröbner-bases','identfcensoringdecentralized-learningdelayed-feedbackdiscretizationfederated-learninggeometric-temperinggradient-flowheat-diffusionmachine-learningonline-learningprivacystatistical-learningsurvival-analysis
Paper metadata
- arXiv ID
- 2604.20296
- 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
- 7135ddeb0bf64d89f5a07f35fe0aaa4d8021f0ec9a3eaef5a57adfc53f1d5c2b
- Enrichment time
- 2026-04-23T07:23:59Z
- AI-assisted enrichment
- Yes
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