What is a potential drawback of using the Adagrad optimization algorithm in logistic regression training over an extended period?

A$)$ The learning rates might become too large, leading to divergent behavior.

B$)$ The cumulative sum of squared gradients in the denominator might cause learning rates to shrink excessively, nearly halting learning.

C$)$ The algorithm excessively focuses on minimizing bias rather than variance.

D$)$ The model parameters might reset spontaneously during training.