All Questions
Tagged with machine-learning dg.differential-geometry
5
questions
6
votes
0
answers
181
views
What are compact manifolds such that GROWTH (of spheres volumes) is well approximated by the Gaussian normal distribution?
Consider some compact Riemannian manifold $M$. Fix some point $p$.
Consider a "sub-sphere of radius $r$" - i.e. set of points on distance $r$ from $p$.
Consider growth function $g(r)$ to be ...
4
votes
1
answer
440
views
Ricci flow for manifold learning
I know that mean curvature and diffusion-type flows are common in manifold learning because of their smoothing effects. I haven't seen Ricci flow used as much. Given that Ricci and diffusion-type ...
37
votes
8
answers
19k
views
How useful is differential geometry and topology to deep learning?
After seeing this article https://www.quantamagazine.org/an-idea-from-physics-helps-ai-see-in-higher-dimensions-20200109/ I wanted to ask myself how useful of an endeavor would it be if one goes ...
23
votes
1
answer
4k
views
Relation between information geometry and geometric deep learning
Disclaimer: This is a cross-post from a very similar question on math.SE. I allowed myself to post it here after reading this meta
post about cross-posting between mathoverflow and math.SE, I did
...
1
vote
0
answers
187
views
Solution to a Strongly Convex Non-smooth Minimization Problem involving an L1 Norm
Let $X \in \mathbb{R}^{n \times d}, w \in \mathbb{R}^d, y \in \{\pm 1\}^{n}, \alpha \in [0,1], \lambda \in \mathbb{R}$. I have an expression that looks as follows
$\frac{1}{2}\|Xw -y \|_{2}^2 + \...