Logo

MINDS Seminar - Eli Sherman - Shared screen with speaker view
Ilya Shpitser
26:55
parameter theta is identified if it is a unique functional of the observed data distribution.
Jeremias Sulam
27:26
got it, thanks!
Ilya Shpitser
31:52
Judea also calls it the ‘structural causal model.’
Ilya Shpitser
35:47
if you are curious, this is the paper Eli is referring to:
Ilya Shpitser
35:48
https://rss.onlinelibrary.wiley.com/doi/full/10.1111/1467-9868.00340
Jeremias Sulam
42:15
these sides comments are awesome
Ilya Shpitser
01:11:13
semi-parametric inference: estimating parameters without having to specify a parametric likelihood (which will lead to problems if it’s wrong). Search is trying to use data to help you figure out what graph to use (which is a precondition for work Eli discussed).
Yanxun Xu
01:11:53
Thanks, Eli! Great talk!
Ilya Shpitser
01:15:50
Data fusion is important to deal with for these global problems like COVID-19 — where there is no one model that faithfully represents different jurisdictions (even though they have commonalities).
Ilya Shpitser
01:16:22
In other words, NYC and Italy are similar, but it’s probably not reasonable to have a single causal model — so how do we use multiple models?
Ilya Shpitser
01:16:39
Elias Barenboim is a leading causal researcher on this problem (although we are starting to think about this stuff also).