Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization · HackerPapers discussionshttps://hackerpaper.kaipfister.de/p/2006.05078/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMTDifferentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization — mentioned by mccourthttps://news.ycombinator.com/item?id=23793847urn:hackerpapers:mention:2006.05078:23793847Fri, 10 Jul 2020 17:19:28 GMT<p>This blog post lists a bunch of gradient-free optimization packages, some genetic and some Bayesian: https://sigopt.com/blog/comparison-bayesian-packages-hyperpa.... Nothing from the mathematical programming community in here, so definitely other options too (depending on what kind of problems you are trying to address). Personally, I like Nevergrad (https://facebookresearch.github.io/nevergrad/) a lot for general purpose optimization problems -- I think it is very well implemented and has a variety of tools available. I also think the documentation is appropriately honest about what is and…</p><p><a href="https://hackerpaper.kaipfister.de/p/2006.05078/">Paper and discussion history</a>. A mention is not an endorsement.</p>stat.ML