Replication Data for: On the Universality of the Double Descent Peak in Ridgeless Regression

DOI

This dataset contains code used to generate the figures in the paper On the Universality of the Double Descent Peak in Ridgeless Regression, David Holzmüller, International Conference on Learning Representations 2021. The code is also provided on GitHub. Here, we additionally provide the data that is generated by the code and that is required to generate the plots. To use this data, simply unpack the (large!) file data.tar.gz inside the folder where the Python files are located. If the data is not downloaded and unpacked, the code will automatically compute it, which can take about one day on a 6-core-CPU. Information on the code and used software can be found in the file README.md.

Identifier
DOI https://doi.org/10.18419/darus-1771
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/darus-1771
Provenance
Creator Holzmüller, David ORCID logo
Publisher DaRUS
Contributor Holzmüller, David; Steinwart, Ingo
Publication Year 2021
Rights Apache 2.0; info:eu-repo/semantics/openAccess; https://www.apache.org/licenses/LICENSE-2.0
OpenAccess true
Contact Holzmüller, David (Universität Stuttgart); Steinwart, Ingo (Universität Stuttgart)
Representation
Resource Type Dataset
Format text/x-python; application/gzip; text/markdown
Size 16572; 5968223388; 2733; 15678; 1684; 11414; 2682
Version 1.0
Discipline Other