3 ms·
> In computer vision, geometry describes the structure and shape of the world. Specifically, it concerns measures such as depth, volume, shape, pose, disparity,
by santaclaus 10y ago
> In computer vision, geometry describes the structure and shape of the world. Specifically, it concerns measures such as depth, volume, shape, pose, disparity, motion or optical flow.
Isn't optimization geometry? DL is just shifting the requisite geometric insights to a different level of abstraction. Take that knowledge of geometry, revolutionize non-convex optimization, and let all fields that build on the base abstraction benefit.
- deepnotderp 10y agoDL's optimization is pretty simple SGD. But I would suggest that the type of optimization in deep learning is actually a lot more like geometry than calculus. This was more of a hunch until recently, but some results such as the successful application of tropical geometry and less exotic Riemannian geometry to the analysis of DL loss surfaces are showing some evidence for that hypothesis.