Adapts bandit algorithms to the Cox PH survival model for online treatment optimization under censoring, with theoretical sublinear regret and validation on simulations plus SEER cancer data.
International Conference on Artificial Intelligence and Statistics , pages=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
stat.ML 2years
2026 2representative citing papers
citing papers explorer
-
Online Survival Analysis: A Bandit Approach under Cox PH Model
Adapts bandit algorithms to the Cox PH survival model for online treatment optimization under censoring, with theoretical sublinear regret and validation on simulations plus SEER cancer data.
- Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and Safety