ayidnelm
Re:Introduction to tangzhong (2018)
on Wednesday April 01, 2020 @06:23AM (#22747276)
Which thread was this, if you don't mind?
Re:Stop Explaining Black Box Models for High Stakes Decisions
on Friday November 01, 2019 @07:23AM (#21417693)
It's a good line, what is the context / source for that quote?
Re:Uber lays off around 350 more across Eats, self-driving and other d...
on Monday October 14, 2019 @06:02PM (#21253363)
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.
Re:AutoML toolkit for neural architecture search and hyper-parameter t...
on Friday March 01, 2019 @07:01AM (#19279748)
There's also auto scikit-learn https://github.com/automl/auto-sklearn if you haven't already come across that.
Re:Unifying Logical and Statistical AI (2006) [pdf]
on Saturday January 12, 2019 @06:17AM (#18890727)
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.
Re:9999999999999999.0 – 9999999999999998.0
on Sunday January 06, 2019 @05:31PM (#18841164)
> 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.
Re:How I Transitioned from Physics Academia to the ML Industry
on Wednesday October 10, 2018 @04:24AM (#18183001)
I think Jeffreys, Wald and Savage had all started on advocating Bayesian statistics/probability before Jaynes.