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collaborative-filtering-on-movielens-10m

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PaperCodeRMSEMAP@15MAP@30MAP@5NDCG@15NDCG@30NDCG@5HR@10HR@100PSP@10nDCG@10nDCG@100ModelNameReleaseDate
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems✓ Link0.7485Bayesian timeSVD++ flipped2019-05-04
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems✓ Link0.7523Bayesian timeSVD++2019-05-04
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems✓ Link0.7563Bayesian SVD++2019-05-04
Mixture-Rank Matrix Approximation for Collaborative Filtering✓ Link0.7634MRMA2017-12-01
Kernelized Synaptic Weight Matrices✓ Link0.769Sparse FC2018-07-01
A Neural Autoregressive Approach to Collaborative Filtering✓ Link0.771CF-NADE2016-05-31
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems✓ Link0.772SGD MF2019-05-04
Hybrid Recommender System based on Autoencoders✓ Link0.7767I-CFN2016-06-24
Graph Convolutional Matrix Completion✓ Link0.777GC-MC2017-06-07
AutoRec: Autoencoders Meet Collaborative Filtering✓ Link0.782I-AutoRec2015-05-18
A federated graph neural network framework for privacy-preserving personalization✓ Link0.793FedPerGNN2022-06-02
Hybrid Recommender System based on Autoencoders✓ Link0.7954U-CFN2016-06-24
Dictionary Learning for Massive Matrix Factorization✓ Link0.799Factorization with dictionary learning2016-05-03
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation0.803FedGNN2021-02-09
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems✓ Link0.823U-RBM2019-05-04
The complementarity of a diverse range of deep learning features extracted from video content for video recommendation✓ Link0.15680.16710.15360.25460.29710.1846scaled-CER2020-11-21
SVD-AE: Simple Autoencoders for Collaborative Filtering✓ Link0.36760.6480.04930.37750.4697SVD-AE2024-05-08
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