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Showing 1 to 1 of 1 for “"matrix facterization"”.
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Quantitative convergence analysis of dynamical processes in machine learning
… and non-Lipschitz-smooth potential functions in matrix factorization problems minimized by gradient descent (GD) with large learning rates, which is beyond the scope of classical optimization theory. We develop a new convergence analysis to show that the large learning rate biases GD towards …