Online Survival Analysis: A Bandit Approach under Cox PH Model
Survival analysis is a widely used statistical framework for modeling time-to-event data under censoring. Classical methods, such as the Cox proportional hazards (Cox PH) model, offer a semiparametric approach to estimating the effects of covariates on the hazard function. Despite its importance, survival analysis has been largely unexplored in online settings, particularly within the bandit framework, where decisions must be made sequentially to optimize treatments as new data arrive over time. In this work, we take an initial step toward integrating survival analysis into a purely online learning setting under the Cox PH model, addressing key challenges including staggered entry, delaye...
| Authors | Yang Xu, Wenbin Lu, Rui Song |
|---|---|
| Primary category | stat.ML |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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