Stability of Stochastic Gradient Method with Momentum for Strongly Convex Loss Functions

While momentum-based methods, in conjunction with the stochastic gradient descent, are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In practice, the momentum parameter is often chosen in a heuristic fashion with little theoretical guidance... (read more)

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