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marco_z

7 karma · joined July 7, 2021

Founder @ UnfoldML

github.com/ocramz

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marco_z··on Ask HN: How did you learn to debug production incidents?
Through tears and mud, how else?
marco_z··on Show HN: Chess on a Donut/Torus and Deep-Dive
E.g the pieces from the rows you eliminate reappear at random at the top row.
marco_z··on Ambsheets: Spreadsheets for Exploring Scenarios
probably one needs something like lazy evaluation, so that things are only computed if needed.
marco_z··on Minimum bipartite matching via Riemann optimization (2023)
Boumal was advised by Absil IIRC :) And in fact you can see this in his more modern presentation of the material.
marco_z··on Minimum bipartite matching via Riemann optimization (2023)
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.
marco_z··on Minimum bipartite matching via Riemann optimization (2023)
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.

marco_z··on Minimum bipartite matching via Riemann optimization (2023)
Yes, the problem can now be solved efficiently with a scikit one-liner, but the aim of this post was more speculative rather than beating the benchmark :)
marco_z··on Minimum bipartite matching via Riemann optimization (2023)
Author here! Thank you f1shy for sharing.
marco_z··on Show HN: Kachika – "Learning Japanese Through Life"
Sugoi! I imagine this approach would be very useful in learning any other language, too.
marco_z··on Minimum bipartite matching via Riemann optimization
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.

marco_z··on Show HN: Piazza, syncing the web in a vectorized DB
same for me now.
marco_z··on Show HN: ColoringsAI – Custom Coloring Pages from Ideas (My Daughter's Idea)
Hi there, while the word list will help, I think plugging an LLM to a user-facing form is still a very, very bad idea, especially if this is meant for children.
marco_z··on Vector: A high-performance observability data pipeline
> 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.