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A Hessian-Vector Product from Two Gradients

Chapter 11 · Mathematics for AI and Machine Learning · Advanced · 1:38

A narrated live film: the difference of two gradients, divided by epsilon, closes in on H d as epsilon shrinks; scrub to replay it.

Narration

Here is a loss surface in two dimensions, a point x, and a direction d. The blue arrow is the gradient at x. Now nudge x by epsilon along d, and draw the gradient there: the teal arrow.

The change in the gradient, divided by epsilon, is the amber arrow. As epsilon shrinks, it settles onto H times d, the Hessian vector product, drawn as the dashed arrow. We never formed H.

The rest of the narration is in the book's Companion.

More from Chapter 11

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