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SOTA
Recommendation Systems
Collaborative Filtering On Movielens 10M
Collaborative Filtering On Movielens 10M
평가 지표
RMSE
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
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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