Predicting the Learning Rate of Gradient Descent for Accelerating Matrix Factorization

Autor: Nóbrega, Caio B., Marinho, Leandro B.

Publikováno v: Journal of Information and Data Management; v. 5, n. 1 (2014): JOURNAL OF INFORMATION AND DATA MANAGEMENT; 94
Journal of Information and Data Management; Vol 5 No 1 (2014): JOURNAL OF INFORMATION AND DATA MANAGEMENT; 94
Journal of Information and Data Management; v. 5 n. 1 (2014): JOURNAL OF INFORMATION AND DATA MANAGEMENT; 94

Matrix Factorization (MF) has become the predominant technique in recommender systems. The model parameters are usually learned by means of numerical methods, such as gradient descent. The learning rate of gradient descent is typically set to lower v

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https://seer.ufmg.br/index.php/jidm/article/view/283