Integrity report for Exploiting random projections and sparsity with random forests and gradient boosting methods -- Application to multi-label and multi-output learning, random forest model compression and leveraging input sparsity

A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.

arXiv:1704.08067 · pith:2017:ECQWZFAQCLXWONVRPP2AICG42M

Paper page arXiv integrity.json bundle.json

Detector runs

Findings

Signed record

The machine-readable record for this paper lives at /pith/ECQWZFAQCLXWONVRPP2AICG42M/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.