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SotA/Knowledge Base/Recommendation Systems/MovieLens 10M

Recommendation Systems on MovieLens 10M

Metric: RMSE (lower is better)

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#Model↕RMSE▲Extra DataPaperDate↕Code
1Bayesian timeSVD++ flipped0.7485NoOn the Difficulty of Evaluating Baselines: A Stu...2019-05-04Code
2Bayesian timeSVD++0.7523NoOn the Difficulty of Evaluating Baselines: A Stu...2019-05-04Code
3Bayesian SVD++0.7563NoOn the Difficulty of Evaluating Baselines: A Stu...2019-05-04Code
4MRMA0.7634No--Code
5Sparse FC0.769No--Code
6CF-NADE0.771NoA Neural Autoregressive Approach to Collaborativ...2016-05-31Code
7SGD MF0.772NoOn the Difficulty of Evaluating Baselines: A Stu...2019-05-04Code
8I-CFN0.7767NoHybrid Recommender System based on Autoencoders2016-06-24Code
9GC-MC0.777NoGraph Convolutional Matrix Completion2017-06-07Code
10I-AutoRec0.782No--Code
11FedPerGNN0.793No--Code
12U-CFN0.7954NoHybrid Recommender System based on Autoencoders2016-06-24Code
13Factorization with dictionary learning0.799NoDictionary Learning for Massive Matrix Factoriza...2016-05-03Code
14FedGNN0.803NoFedGNN: Federated Graph Neural Network for Priva...2021-02-09-
15U-RBM0.823NoOn the Difficulty of Evaluating Baselines: A Stu...2019-05-04Code