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Luke2642 36 minutes ago [-]
This is a great example of why p=np is sometimes the wrong question. For this np hard problem approximate solutions are good enough, and if you get them 45x faster that's even better!
hinkley 17 minutes ago [-]
The best class of algorithms in this category are those where you know for certain that one answer is impossible and the other is highly probable. Like Bloom Filters, and if you squint, consistent hashing. I wish we had more algorithms of this sort and books about them. If I were a professor I’d be tempted to propose teaching a class.
When I was just starting out, client-server was still a bit of a specialty, mostly reserved for gaming and large institutions. Most of my education was in single task computing. If the university hadn’t offered a class in distributed computing I wouldn’t have gotten much in that direction except in independent study.
In the time since then, we seem to have focused much less on seconds per task and more on tasks per second, which results in more concern about statistical spreads, and queuing mechanisms to manage the variability between a hit and a miss. It would be better if this sort of computation were more organized into a discipline.
Luke2642 5 minutes ago [-]
My personal favourite is compressive sensing, sparse signals beat the Nyquist sampling limit, by what seems like an unbounded amount 1000x, 1000000x, etc, because all real world stuff we care about lives on a low dimensional manifold, so unlike the noise.
LPisGood 14 minutes ago [-]
The entire field of operations research is essentially founded on the premise that NP hard is just a starting place.
real_faxenoff 1 hours ago [-]
I adapted the method to my IVF index (the code-daemon project) and achieved a 146x speedup on the GPU.
That's impressive!
wood_spirit 2 hours ago [-]
This looks awesome. Obvious in hindsight! The viz really explains it well.
Hope it gets added to scipy - it’s much more available in the envs many use than facebooks own faiss library.
porridgeraisin 1 hours ago [-]
The automatic hyperparameter laws don't seem intuitive to me yet. Do you have any intuition for it?
bashhq_r 25 minutes ago [-]
so the epoch reduction is cool but the hyperparameter laws feel like they were fit post-hoc
When I was just starting out, client-server was still a bit of a specialty, mostly reserved for gaming and large institutions. Most of my education was in single task computing. If the university hadn’t offered a class in distributed computing I wouldn’t have gotten much in that direction except in independent study.
In the time since then, we seem to have focused much less on seconds per task and more on tasks per second, which results in more concern about statistical spreads, and queuing mechanisms to manage the variability between a hit and a miss. It would be better if this sort of computation were more organized into a discipline.
That's impressive!
Hope it gets added to scipy - it’s much more available in the envs many use than facebooks own faiss library.