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How do advanced optimization algorithms, such as stochastic gradient descent with momentum or Adam optimization, expedite the convergence of large-scale classification models while avoiding local

How do advanced optimization algorithms, such as stochastic gradient descent with momentum or Adam optimization, expedite the convergence of large-scale classification models while avoiding local optima?

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