/explore
|
You are here 
|
arachnoid.com | ||
| | | | |
mathwithbaddrawings.com
This generalizes, of course, to the Theorem of How You Learn Stokes' Theorem. |
|
| | | | | ||
| | | | |
alexkritchevsky.com
|
|
| | | | | ||
| | | | |
mmph.wordpress.com
The recent post on cloud computing and Google Docs made me ask myself whether Google Docs supports (La)TeX. It turned out you can insert LaTeX equations into your Google doc (as discussed in more detail e.g. here) but that's that for now. There exists a LaTeX Lab project aspiring to develop a web-based LaTeX editor... |
|
| | | | | ||
| | | | |
francisbach.com
[AI summary] This text discusses the scaling laws of optimization in machine learning, focusing on asymptotic expansions for both strongly convex and non-strongly convex cases. It covers the derivation of performance bounds using techniques like Laplace's method and the behavior of random minimizers. The text also explains the 'weird' behavior observed in certain plots, where non-strongly convex bounds become tight under specific conditions. The analysis connects theoretical results to practical considerations in optimization algorithms. |
|
| | | |||
