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Yes! Cvxpy 1.0 now detects QPs and avoids the slow SOCP reduction. Also, it exploits OSQP to perform factorization caching and warm starting. If you solve param

Yes! Cvxpy 1.0 now detects QPs and avoids the slow SOCP reduction. Also, it exploits OSQP to perform factorization caching and warm starting. If you solve parametric QPs in a sequence (e.g., lasso pareto frontier) the speedups are even bigger. It would be very interesting to try the Anderson acceleration for QPs! We tried other line search methods but they did not bring consistent improvements for different problems. I think Anderson acceleration could be more useful (also from the theoretical point of view). Could you put me in touch with the person working on that in the lab? I would be happy to try it. We have a prototype Python implementation that could be used for that.

LolWolf 9y ago
Yay! That's awesome, I'm glad (this was a bit of a problem with last year's EE364A exam, actually, since the solver for a problem was too slow, so we decided to not include it). The benchmarks are quite impressive as well! Anyways, one of the TAs for 364 was working on it---I believe under Boyd, but unsure; I can ask if it was specifically SOCPs, which is what I recall---and I'm also applying it to certain other large-scale (but non-convex) cases. I'll ask him and get back to you on that. My profile has my email, if you'd like to not dox yourself as well, and I can put you two in touch.