[jl2718]

I started from zero, and my approach was to read Nocedal/Wright cover-to-cover, and then the same with "Numerical Linear Algebra" by Trefethen/Bau. Usually it goes the other way, but I found the linear algebra primer in N/W to be good enough to get started.

I also read "Practical Optimization" by Murray/Gill, which is interesting because it has a lot of conversational coverage of e.g. corner cases, stuff that most textbooks won't cover.

That will cover the expected baseline of almost everything you'll encounter in the convex smooth continuous domain. I don't have great answers for moving past that.

[jl2718]

I may have found the answer: https://link.springer.com/referencework/10.1007/978-0-387-74...