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Models/RaCT

RaCT

Reported on 9 benchmarks across 1 task · 1 paper · 4 SOTA

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

Knowledge Base9 results

Recommendation SystemsonMovieLens 20M
Recall@20· 2019-06-10
0.403
best: 0.418 (Multi-Gradient Descent)
SOTA
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281
Recommendation SystemsonMovieLens 20M
Recall@50· 2019-06-10
0.543
best: 0.553 (RecVAE)
SOTA
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281
Recommendation SystemsonMovieLens 20M
nDCG@100· 2019-06-10
0.434
best: 0.448 (VASP)
SOTA
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281
Recommendation SystemsonNetflix
Recall@50· 2019-06-10
0.45
best: 0.46252 (H+Vamp Gated)
SOTA
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281
Recommendation SystemsonMillion Song Dataset
Recall@20· 2019-06-10
0.268
best: 0.333 (EASE)
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281
Recommendation SystemsonMillion Song Dataset
Recall@50· 2019-06-10
0.364
best: 0.428 (EASE)
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281
Recommendation SystemsonMillion Song Dataset
nDCG@100· 2019-06-10
0.319
best: 0.389 (EASE)
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281
Recommendation SystemsonNetflix
Recall@20· 2019-06-10
0.357
best: 0.37678 (H+Vamp Gated)
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281
Recommendation SystemsonNetflix
nDCG@100· 2019-06-10
0.392
best: 0.40861 (H+Vamp Gated)
Towards Amortized Ranking-Critical Training for Collaborative Filtering arXiv:1906.04281