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Just curious what are the deeper optimization topics you were hoping to see in the monograph?

Shameless plug: I hold a lecture on "Optimization Methods for Machine Learning" that goes deep into convex optimization.

Video recordings from the corona period (+ slides) are available here: https://www.youtube.com/playlist?list=PLdkTDauaUnQpzuOCZyUUZ...

Thank you... I'm going to check out your videos and slides.

Not OP, but probably Convex Optimization [1].

Or maybe branch-and-bound? Useful but not that mathematical.

Judging from the TOC, everything in Part I of Boyd and Vandenberghe appears in some form in the monograph, so I don't think that's it.