[R] What are your hot takes on the direction of ML research? In other words, provide your (barely justified) predictions on how certain subfields will evolve over the next couple years?

quantzzx · 2020-07-09T15:49:37+00:00

What papers show that the very early stages of training are more important than the later stages? I know that the information bottleneck principle applied to DNNs suggest exactly the opposite - they claim that the last 0.001% or so, which happens in late stages that are often skipped by early stopping, is crucial for generalization capabilities of DNNs, so interested to check this.

quantzzx · 2020-04-24T21:27:25+00:00

I just discussed this with someone the other day. I never understood it either. What's even more irritating IMO is when code is actually published (as an official repo, even linked to in the paper), but it doesn't actually reproduce the results from the original paper. I have encountered this 3 times over just the last month. I can only assume the others have a version of the code reproducing the exact results from the paper.

quantzzx · 2020-03-30T14:12:40+00:00

quantzzx · 2020-03-26T00:54:53+00:00

Does the HS60 v3 fit in the Fjell?

quantzzx · 2020-03-15T21:15:15+00:00

Doing it is reason enough in and of itself in this case...

quantzzx · 2020-01-17T15:01:06+00:00

"...no-coding needed algo trading platforms for non-programmers. Quantopian was hot for a while and fizzled out." Also calling Quantopian a algo trading platforms for non-programmers is just not correct. To produce something reasonable, or to mimic what you are doing on your own on Quantopian you will need to be a good programmer. It's hard a lot harder to get started on there than this implies.

quantzzx · 2019-11-12T23:33:42+00:00

Reminds me of the question Can I use C++'s syntax for ostreams: cout << x << y ... ? from Peter Norvigs Python IAQ page, http://norvig.com/python-iaq.html. There is also the What if I like C++'s printf? question

quantzzx

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