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Meta-learning with generalized ridge regression: High-dimensional asymptotics, optimality and hyper-covariance estimation
Meta-learning involves training models on a variety of training tasks in a way that enables
them to generalize well on new, unseen test tasks. In this work, we consider meta-learning …
them to generalize well on new, unseen test tasks. In this work, we consider meta-learning …
HEDE: Heritability estimation in high dimensions by Ensembling Debiased Estimators
Estimating heritability remains a significant challenge in statistical genetics. Diverse
approaches have emerged over the years that are broadly categorized as either random …
approaches have emerged over the years that are broadly categorized as either random …
On high-dimensional asymptotic properties of model averaging estimators
R Ando, F Komaki - arxiv preprint arxiv:2308.09476, 2023 - arxiv.org
When multiple models are considered in regression problems, the model averaging method
can be used to weigh and integrate the models. In the present study, we examined how the …
can be used to weigh and integrate the models. In the present study, we examined how the …