Adam: A Method for Stochastic Optimization
At a glance
Adam automatically adjusts learning rates to guide neural-network training.
In one paragraph
Adam adjusts how much each model parameter changes during training, using recent learning signals to guide the updates. It combines efficient computation with modest memory needs and little tuning, offering a practical training method for large datasets and noisy learning signals.
