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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Scalable Approximate Model Counter · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1306.5726/</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/1306.5726/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Scalable Approximate Model Counter — mentioned by zero_k</title><link>https://news.ycombinator.com/item?id=43093934</link><guid isPermaLink="false">urn:hackerpapers:mention:1306.5726:43093934</guid><pubDate>Tue, 18 Feb 2025 19:26:16 GMT</pubDate><description>&lt;p&gt;But you forgot! It&amp;#x27;s also a 3-wise independent linear hashing function! Which means it can be used for probabilistically approximately uniform sampling and counting of solutions to boolean functions. This is super-duper useful. We use it to build counters that give probabilistic, but proven, counts. I explained the idea here in more understandable terms [1]. Basically, it halves the solution space approximately correctly each time. So you keep on adding them, until you have say, 10 solutions. Then you multiply the 10 with 2^k, where k is the number of XORs you added. That&amp;#x27;s it! So cool, no?…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1306.5726/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LO</category></item></channel></rss>
