Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
|
Daily Overview |
| Session | |
|
Computational Biostatistics Location: 1.012 Session Chair: Dennis Dobler | |
    | |
Robust Feature Selection for High-Dimensional Mixtures of Cox Models University of Augsburg, Germany Time-to-event analysis is fundamental for studying patient survival in modern biomedical research, particularly in the presence of high-dimensional covariate information. When survival data are collected over long time horizons, population heterogeneity naturally arises due to evolving clinical practices and patient characteristics. Mixtures of Cox proportional hazards models offer an effective way to account for such heterogeneity by modeling latent subpopulations with distinct risk profiles. In high-dimensional settings, feature selection is crucial for improving model interpretability and predictive performance. This talk presents a robust feature selection approach for mixtures of Cox models based on a combined ℓ1–ℓ2 penalty, which encourages sparsity while stabilizing estimation across mixture components. The resulting optimization problem is non-smooth and challenging to solve within mixture models. We address this challenge by developing an efficient Expectation–Maximization (EM) algorithm that effectively handles the non-smooth penalty structure. Empirical results demonstrate that the proposed method improves patient-specific survival time prediction across heterogeneous populations while achieving stable and interpretable feature selection. | |
