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cs.LG2021★ 1 cited
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders
Oskar Allerbo, Rebecka Jörnsten
High-dimensional data sets are often analyzed and explored via the construction of a latent low-dimensional space which enables convenient visualization and efficient predictive mo…
cs.LG2020
Flexible, Non-parametric Modeling Using Regularized Neural Networks
Oskar Allerbo, Rebecka Jörnsten
Non-parametric, additive models are able to capture complex data dependencies in a flexible, yet interpretable way. However, choosing the format of the additive components often re…