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ayidnelm

10 karma · joined October 10, 2018

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ayidnelm··on Introduction to tangzhong (2018)
Which thread was this, if you don't mind?
ayidnelm··on Stop Explaining Black Box Models for High Stakes Decisions
It's a good line, what is the context / source for that quote?
ayidnelm··on Uber lays off around 350 more across Eats, self-driving and other departments
As my sibling poster indicates, the SO survey is a convenience sample not a census of coders. If you look at the 2016 survey, the 0-5 years experience cohort is larger (50.3%) than than it is in 2019, so I am not sure we can make those kinds of conclusions about the wider industry.
ayidnelm··on AutoML toolkit for neural architecture search and hyper-parameter tuning
There's also auto scikit-learn https://github.com/automl/auto-sklearn if you haven't already come across that.
ayidnelm··on Unifying Logical and Statistical AI (2006) [pdf]
Lise Getoor have a nice talk at NIPS in 2017 on a what I think is a formalism, Probabilistic Soft Logic, that her group developed: https://youtu.be/t4k5LKCpboc . Definitely an interesting direction of research.
ayidnelm··on 9999999999999999.0 – 9999999999999998.0
> Floating point numbers are the optimal minimum message length method of representing reals with an improper Jeffery's prior distribution.

Do you have a link to a proof or discussion of this? I haven't heard this before and I would love to have this statement unpacked a little more.

ayidnelm··on How I Transitioned from Physics Academia to the ML Industry
I think Jeffreys, Wald and Savage had all started on advocating Bayesian statistics/probability before Jaynes.