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What is VAE vs DAE in Recommender Systems about?

This paper compares Variational Autoencoders (VAE) and Denoising Autoencoders (DAE) for collaborative filtering in recommender systems, highlighting their strengths in handling different dataset sizes. VAE performs better on large datasets due to its ability to capture complex patterns, while DAE is more effective on smaller datasets by reconstructing original inputs from noisy data. The study evaluates both methods using three public datasets and various metrics, concluding that deep learning techniques ca

Author

hiba

Language

EN