My understanding of ML interpretability research at the moment is that it's very early days - too early, perhaps, to hope for a general purpose compressor algorithm that produces proofs of it's own workings (that seems like the holy grail). But of course I would love to be wrong!
Mathematicians led by Terence Tao are keen to explore new ways for mathematicians to collaborate remotely and online to tackle all open problems together in an open and technology-supported way. I think problem inventories should be part of that, together with proof collections, existing datasets such as the great On-Line Encyclopedia of Integer Sequences (OEIS, at https://oeis.org), and perhaps Jupyter-type notebooks that utilize symbolic algebra systems, theorem provers etc.
wrsh07•3h ago
All three authors are large contributors to the field (the book _discrete and computational geometry_ by O'Rourke & Devadoss is excellent), Demaine has some origami in the collection at MoMA NYC^, Mitchell found a ptas for euclidian tsp (Google it - the paper is readable and there is another good write up of his vs Arora's)
^ https://erikdemaine.org/curved/MoMA/
yorwba•1h ago
jll29•1h ago
boxfire•58m ago
If it's not been already there's immediate application, e.g. problem 41.
[1]:https://link.springer.com/article/10.1007/s00453-015-0079-6