Wide&Deep

Reported on 2 benchmarks across 1 task · 1 paper · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Miscellaneous2 results

Click-Through Rate PredictiononCriteo
AUC· 2016-06-24
0.7981
best: 0.8163 (QNN-α)
SOTA
Wide & Deep Learning for Recommender Systems arXiv:1606.07792
Click-Through Rate PredictiononCriteo
Log Loss· 2016-06-24
0.46772
best: 0.4358 (QNN-α)
Wide & Deep Learning for Recommender Systems arXiv:1606.07792