🏢 Munich Center for Machine Learning (MCML)
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization
·4058 words·20 mins·
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AI Theory
Optimization
🏢 Munich Center for Machine Learning (MCML)
Reshuffling data splits during hyperparameter optimization surprisingly improves model generalization, offering a computationally cheaper alternative to standard methods.
A Functional Extension of Semi-Structured Networks
·2279 words·11 mins·
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Machine Learning
Deep Learning
🏢 Munich Center for Machine Learning (MCML)
This paper introduces semi-structured functional networks (SSFNNs), a novel approach that combines interpretable functional regression models with deep neural networks, achieving both high accuracy an…