What is an Adaptive Step Size in Parameter Estimation?

An adaptive step size is like adjusting your speed while walking to reach a destination faster or slower depending on how far you have to go.

Imagine you're trying to get from your house to the park, and you don’t know exactly how far it is. You start by taking big steps, maybe 10 at a time, but after a few steps, you realize you’re going too fast and might overshoot the park. So you slow down, taking smaller steps, like 5 at a time, to be more careful.

This is what adaptive step size does in parameter estimation: it changes how big or small each guess (or step) is when trying to find the right answer. If the estimate is moving too fast and missing the mark, it slows down. If it’s getting closer, it might speed up a bit, like walking faster when you're almost at the park.

Without adaptive step size, you’d always take the same number of steps, big or small, no matter how close you are to your goal. That can make things slower or less accurate, just like always taking 10 steps even when you’re only a few away from the park.