By Yinggan XU Dibbla This is generated by a previous courses (not included in Lee’s 2022 series), video can be found: CNN The motivation is that we can of course use MLP to find a function such that we do image classification etc. However, it’s not necessary and not efficient due to the tremendous number of parameters. We are going to use the properties of images themselves. Before that, we need to know the structure of a picture....
By Yinggan XU Dibbla The tutorial video can be found here This notebook will only cover the basic optimizers and their ideas. However, the optimizers for DL remains a very interesting question. Background Knowledge $\mu$-strong Convexity We can refer to this note. A function $f$ is $\mu$-strong convex if: $$f(y)\ge f(x)+\nabla f(x)^T(y-x) + \frac{\mu}{2}||y-x||^2\newline \text{for some $\mu\ge0$ and for all $x,y$}$$ Note that Strong convexity doesn’t necessarily require the function to be differentiable, and the gradient is replaced by the sub-gradient when the function is non-smooth....