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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1202.3764/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1202.3764/feed.xml" rel="self" type="application/rss+xml" /><item><title>Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective — mentioned by null08</title><link>https://news.ycombinator.com/item?id=41447155</link><guid isPermaLink="false">urn:hackerpapers:mention:1202.3764:41447155</guid><pubDate>Wed, 04 Sep 2024 15:47:45 GMT</pubDate><description>&lt;p&gt;I made the first version of this back in 2010, when Pearl&amp;#x27;s work on causal inference started impacting Epidemiology. A friend was an Epidemiologist and she told me about an MS-DOS program she was using to do something with graphs (https://pubmed.ncbi.nlm.nih.gov/20010223/); she found it painfully slow and wondered if I could &amp;quot;make it more user-friendly&amp;quot;. I did my PhD in algorithms at the time and was intrigued when I started reading Greenland, Pearl, and Robins (https://pubmed.ncbi.nlm.nih.gov/9888278/) and then Pearl&amp;#x27;s &amp;quot;Causality&amp;quot;. I soon found that it was not obvious at all how you could…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1202.3764/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
