shurtler

5 ms·

1.
by shurtler 3y ago
Fantastic! Any tips on tools one can use to parse PDF including their structure? Much appreciated.
2.
Ask HN: What use are data scientists when the ground truth is not known?
2 points by shurtler 6y ago|0 comments
3.
by shurtler 8y ago
You will benefit from reading Pearl/Glymour/Jewell: Causal Inference in Statistics. A Primer (The contrast to Imbens and Rubin is crazy)
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Model-Free, Model-Based, and General Intelligence [pdf](ijcai.org)
91 points by shurtler 8y ago|31 comments
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A Nobel-winning economist’s guide to taming tech monopolies(qz.com)
2 points by shurtler 8y ago|0 comments
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Congressional testimony on Cambrdige Analytica [pdf](eitanhersh.com)
2 points by shurtler 8y ago|0 comments
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Male Sexlessness Is Rising, but Not for the Reasons Incels Claim(ifstudies.org)
49 points by shurtler 8y ago|83 comments
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Network Effects, Big Data, and Antitrust Issues for Big Tech(conversableeconomist.blogspot.com)
3 points by shurtler 9y ago|0 comments
9.
by shurtler 9y ago
This is one the most thought-provoking things I've read on markets and economic policy in a very long while.
10.
Property Is Only Another Name for Monopol(papers.ssrn.com)
2 points by shurtler 9y ago|1 comments
11.
by shurtler 9y ago
Note there's an exploding literature that reads these models as causal models: http://ftp.cs.ucla.edu/pub/stat_ser/r350.pdf
12.
by shurtler 10y ago
Central proposal on p. 98: "What if, instead, knowledge was unbundled from the start and embedded in how researchers actually develop their knowledge? This is essentially what happens with computer code , where programmers are encourag
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Scholarly Publishing and its Discontents(joshuagans.com)
1 points by shurtler 10y ago|1 comments
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The CIA Reads French Theory(thephilosophicalsalon.com)
3 points by shurtler 10y ago|0 comments
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Stop Fabricating Travel Security Advice(medium.com)
4 points by shurtler 10y ago|0 comments
16.
by shurtler 10y ago
"I really like penalized maximum likelihood estimation (which is really empirical Bayes) but once we have a penalized model all of our frequentist inferential framework fails us. No one can interpret a confidence interval for a biased
17.
by shurtler 10y ago
Hey, the key assumption (the "identification" assumption) is in 2.4 of the paper you referred to. I do not have time to go through the notation, but it seems to be like a fairly standard "no unmeasured confounders" assum