HN user

marco_z

7 karma

Founder @ UnfoldML

github.com/ocramz

Posts1
Comments13
View on HN

Good pointer! I did know about CVXPY but haven't used it yet. Though in requiring everything to be (log-)convex it constrains the user programs quite a bit, but I imagine it would have worked in this case because the objective is linear and the feasible set convex. I won't deny the role accident and force of habit had in picking this particular implementation path; I used Pytorch because it's my daily driver :D and because I had found 'mctorch' which provided the Riemann SGD logic.

It's incredible how many algorithms can be made differentiable end-to-end.

E.g. in https://arxiv.org/abs/1905.11885 "Differentiable ranks and sorting using optimal transport" they show how a relaxation of an array sorting procedure leads to differentiable rank statistics (quantiles etc.). The underlying theory is quite close to what I show in the blog post.

In DETR they don't actually use a differentiable Hungarian algorithm, it's only used to score their neural predictions outside of the training loop IIUC.

An interesting connection between combinatorial optimization and differential geometry. And some Pytorch too, because when all you have is a hammer..

I built most of this one year ago, but only now managed to write it up. I enjoyed the change of pace of a pure speculative experiment (with some deep connections to a bunch of interesting theory and applications), and I hope you will enjoy reading about it too.

you could ship logs into Splork, then let it ingest that data into FlorbHut, and then use a frontend like Glorply to search logs

Seriously though, is there a single OSS product that does all of this ? Like, for a small multitenant app (i.e not "web-scale"), and that doesn't force one to get a degree in observability just to get stuff done.