I-CFN

Reported on 3 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.

Knowledge Base3 results

Recommendation SystemsonDouban
RMSE· 2016-06-24
0.6911
SOTA
Hybrid Recommender System based on Autoencoders arXiv:1606.07659
Recommendation SystemsonMovieLens 1M
RMSE· 2016-06-24
0.8321
best: 0.8227 (GLocal-K)
Hybrid Recommender System based on Autoencoders arXiv:1606.07659
Recommendation SystemsonMovieLens 10M
RMSE· 2016-06-24
0.7767
best: 0.7485 (Bayesian timeSVD++ flipped)
Hybrid Recommender System based on Autoencoders arXiv:1606.07659