The reviewed record of science sign in
Pith

Integrity report for Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning

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

arXiv:2109.14729 · pith:2021:UH5LKDUIFHFNC7BAO5FVDZMIJJ

0Critical
0Advisory
0Detectors run
Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/UH5LKDUI/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.