Deep Learning Systems
AdaGrad is an adaptive learning rate optimization algorithm that adjusts the learning rate for each parameter based on the historical gradient information. This means that parameters with larger gradients will have their learning rates decreased more significantly than those with smaller gradients, allowing for efficient training even in sparse data situations. This approach helps to speed up convergence and is particularly useful in scenarios where features exhibit different frequencies of updates.
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