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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Maximally Consistent Sampling and the Jaccard Index of Probability Distributions · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1809.04052/</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/1809.04052/feed.xml" rel="self" type="application/rss+xml" /><item><title>Maximally Consistent Sampling and the Jaccard Index of Probability Distributions — mentioned by moultano</title><link>https://news.ycombinator.com/item?id=23462814</link><guid isPermaLink="false">urn:hackerpapers:mention:1809.04052:23462814</guid><pubDate>Tue, 09 Jun 2020 01:47:56 GMT</pubDate><description>&lt;p&gt;I don&amp;#x27;t have any post graduate education. I&amp;#x27;m ok at math, but not exceptional. I managed to publish a paper a few years ago that is mostly a math paper that I&amp;#x27;m really proud of. https://arxiv.org/abs/1809.04052 (It&amp;#x27;s a useful algorithm for big-data work, but it&amp;#x27;s also a bit of math about how to align probability distributions so they collide as much as possible. I tell my kids that daddy discovered something new about how triangles fit together.) There are lots of useful corners of math out there, lots of things that are worth thinking about that no one has thought about just because there…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1809.04052/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.DS</category></item></channel></rss>
