I’ll be speaking at the workshop on Data-Efficient Machine Learning. And here’s the schedule.

I’ll be speaking on the following topic:

Toward Routine Use of Informative Priors

Bayesian statistics is typically performed using noninformative priors but the resulting inferences commonly make no sense and also can lead to computational problems as algorithms have to waste time in irrelevant regions of parameter space. Certain informative priors that have been suggested don’t make much sense either. We consider some aspects of the open problem of using informative priors for routine data analysis.

I’ll also be speaking on one other, related, thing. And I’ll be part of the panel discussion at 3:30pm.

The workshop will be at the Marriott Marquis (Astor Room), New York.

**P.S.** The slides are here.

This is a an exciting workshop that I’m looking forward to in general. A lot of interesting talks, e.g., Joelle Pineau’s, Brenden Lake’s, and contributed talks on deep generative models with stick-breaking priors or meta-analysis (“neural statistician”).

Andrew: So sorry I just got this notice, I would have loved to attend. Now that I’m mostly in NYC please tell me in advance when you’re speaking. Thank you.

Since you were shilling for yougov the other day you might want to talk about their big miss on Brexit (off by 6% from their eve-of-election poll–remain up 2 on their last poll and leave up by 4 as of this posting).

Could you please post the slides or related paper?

Thanks!

I second that request

I third the motion with extreme prejudice!

I posted the slides; see P.S.

> Please do not tell our employers that we spent any time doing this.

I won’t ;-)

(Click through these – https://sites.google.com/site/dataefficientml/accepted-papers)