A stochastic gradient descent algorithm requires tuning of the learning rate parameter over time. Should we...

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A stochastic gradient descent algorithm requires tuning of the learning rate parameter over time. Should we reduce it over time or increase it over time? Explain either way. B (10 points) Explain intuitively, how the learning rate should be adjusted as a function of the mini-batch size. A stochastic gradient descent algorithm requires tuning of the learning rate parameter over time. Should we reduce it over time or increase it over time? Explain either way. B (10 points) Explain intuitively, how the learning rate should be adjusted as a function of the mini-batch size. A stochastic gradient descent algorithm requires tuning of the learning rate parameter over time. Should we reduce it over time or increase it over time? Explain either way. B (10 points) Explain intuitively, how the learning rate should be adjusted as a function of the mini-batch size. A stochastic gradient descent algorithm requires tuning of the learning rate parameter over time. Should we reduce it over time or increase it over time? Explain either way. B (10 points) Explain intuitively, how the learning rate should be adjusted as a function of the mini-batch size.

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The choice of whether to reduce or increase the learning rate over time in a stochastic gradient descent SGD algorithm depends on the specific charact... View the full answer