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Apologies in advance for being somewhat vague. I'm trying to get pointers to establish a connection between a common trick used in practice in optimization, and the exponential map in differential geometry.

In optimization, we'll sometimes choose to optimise $y = \log x$ instead of $x$ (for positive $x$); one of the perks that this gives is the extra precision and smaller-sized steps around $0$. The idea reminds me of optimising in hyperbolic space - the distance between points grows (as compared to Euclidean) as we move towards zero. The $e^y$ is supposed to map the Euclidean space we optimised in back to the one we care about, a hyperbolic one. That sounds awfully close to the exponential map, a map from the tangent space back to the manifold.

Is there a connection? Does this sound like there must be a connection?

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    $\begingroup$ It's just a change of coordinates. If you're applying, say, gradient descent to one vs. the other what you've effectively done is change the Riemannian metric (defining gradients requires a choice of Riemannian metric which is usually implicit). $\endgroup$ Commented Sep 28, 2020 at 3:11
  • $\begingroup$ thanks @QiaochuYuan . I was hoping that it would be viewed as mapping to the tangent space - rather than a change of coordinates on the current space. Do you have insight on what that particular change of coordinates does? $\endgroup$ Commented Sep 30, 2020 at 15:28

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