Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness

12 Feb 2021 Vien V. Mai Mikael Johansson

Stochastic gradient algorithms are often unstable when applied to functions that do not have Lipschitz-continuous and/or bounded gradients. Gradient clipping is a simple and effective technique to stabilize the training process for problems that are prone to the exploding gradient problem... (read more)

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METHOD TYPE
SGD
Stochastic Optimization
Gradient Clipping
Optimization