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Found 2 papers, 2 papers with code
Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles
Feature bagging is a well-established ensembling method which aims to reduce prediction variance by combining predictions of many estimators trained on subsets or projections of features.
Asymptotics of representation learning in finite Bayesian neural networks
However, our theoretical understanding of how the learned hidden layer representations of finite networks differ from the fixed representations of infinite networks remains incomplete.
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