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Collaborative Filtering On Movielens 10M

Métriques

RMSE

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	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	-

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