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The original was posted on /r/machinelearning by /u/james_stevensson on 2025-09-11 19:22:13+00:00.
Good day everyone, recently I’ve become interested in proofs of convergence for federated (and non-federated) algorithms, something like what’s seen in appendix A of the FedProx paper (one page of it attached below)
I managed to go through the proof once and learn things like first order convexity condition from random blogs, but I don’t think I will be able to do serious math with hackjobs like that. I need to get my math foundations up to a level where I can write one such proof intuitively.
So my question is: What resources must I study to get my math foundations up to par? Convex optimization by Boyd doesn’t go through convergence analysis at all and even the convex optimization books that do, none of them use expectations over the iteration to proof convergence. Thanks for your time
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