This is a great article and its super helpful, thanks to whoever wrote it!
The quadratic sandwich
11–17 of 17 posts
Re: The quadratic sandwich
#12Simplex methods can handle those tough situations, though.
Simplex is not applicable. Simplex only minimises a linear function (f(x)=c'x) under linear inequality constraints (Ax≤b). The minimisation problem here is unconstrained, but (very) non-linear.
Re: The quadratic sandwich
#13It frustrates me when math explainers, and textbooks, seem to start from the "here's why our methods are insufficient to solve our problem" and fail to provide an example of the problem they are trying to solve.
What's the question this method is attempting to answer? What does an answer look like? How does this method lead to it?
> If you have ever tried to minimize a function with gradient descent
"and if otherwise, go kick sand," I guess.
Re: The quadratic sandwich
#14That's my article! Thank you so much to the user who posted it here <3
Re: The quadratic sandwich
#15That's my article! Thank you so much to the user who posted it here <3
Thank you for writing this article! It really helped me clear up my understanding of why you care about min and max eigenvalues of a Hessian matrix, something I've been confused about for some time. I have https://fedemagnani.github.io/math/2025/07/04/fenchel.html queued up to read next (convex conjugates being another topic that confuse the hell out of me).
Re: The quadratic sandwich
#16That's my article! Thank you so much to the user who posted it here <3
Thank you for writing this article! It really helped me clear up my understanding of why you care about min and max eigenvalues of a Hessian matrix, something I've been confused about for some time. I have https://fedemagnani.github.io/math/2025/07/04/fenchel.html queued up to read next (convex conjugates being another topic that confuse the hell out of me).
Haha that's great and excited to hear feedback, thank you so much! In these articles I deliberately want to keep a casual tone, just for grasping the concept, so probably a more rigorous material is very important as a follow-up
Re: The quadratic sandwich
#17Simplex methods can handle those tough situations, though.
Simplex is not applicable. Simplex only minimises a linear function (f(x)=c'x) under linear inequality constraints (Ax≤b). The minimisation problem here is unconstrained, but (very) non-linear.
I guess I wasn't being precise, I meant Nelder-Mead.