Tag: mixed
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Gradient Boosted Mixed Models: Flexible Joint Estimation of Mean and Variance Components for Clustered Data
Gradient Boosted Mixed Models: Flexible Joint Estimation of Mean and Variance Components for Clustered Data arXiv:2511.00217v1 Announce Type: new Abstract: Linear mixed models are widely used for clustered data, but their reliance on parametric forms limits flexibility in complex and high-dimensional settings. In contrast, gradient boosting methods achieve high predictive accuracy through nonparametric estimation, but…
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Using latent representations to link disjoint longitudinal data for mixed-effects regression
Using latent representations to link disjoint longitudinal data for mixed-effects regression arXiv:2510.25531v1 Announce Type: new Abstract: Many rare diseases offer limited established treatment options, leading patients to switch therapies when new medications emerge. To analyze the impact of such treatment switches within the low sample size limitations of rare disease trials, it is important to…
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MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioning
MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioning arXiv:2508.06847v1 Announce Type: new Abstract: High-dimensional Bayesian Optimization (BO) has attracted significant attention in recent research. However, existing methods have mainly focused on optimizing in continuous domains, while combinatorial (ordinal and categorical) and mixed domains still remain challenging. In this paper, we…