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SOTA
Recommendation Systems
Collaborative Filtering On Movielens 10M
Collaborative Filtering On Movielens 10M
评估指标
RMSE
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
RMSE
Paper Title
Repository
SGD MF
0.772
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems
Factorization with dictionary learning
0.799
Dictionary Learning for Massive Matrix Factorization
Bayesian timeSVD++
0.7523
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems
Bayesian SVD++
0.7563
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems
U-CFN
0.7954
Hybrid Recommender System based on Autoencoders
U-RBM
0.823
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems
SVD-AE
-
SVD-AE: Simple Autoencoders for Collaborative Filtering
I-CFN
0.7767
Hybrid Recommender System based on Autoencoders
CF-NADE
0.771
A Neural Autoregressive Approach to Collaborative Filtering
Sparse FC
0.769
Kernelized Synaptic Weight Matrices
scaled-CER
-
The complementarity of a diverse range of deep learning features extracted from video content for video recommendation
Bayesian timeSVD++ flipped
0.7485
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems
FedPerGNN
0.793
A federated graph neural network framework for privacy-preserving personalization
FedGNN
0.803
FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation
-
GC-MC
0.777
Graph Convolutional Matrix Completion
MRMA
0.7634
Mixture-Rank Matrix Approximation for Collaborative Filtering
-
I-AutoRec
0.782
AutoRec: Autoencoders Meet Collaborative Filtering
-
0 of 17 row(s) selected.
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