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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Frugal Streaming for Estimating Quantiles:One (or two) memory suffices · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1407.1121/</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/1407.1121/feed.xml" rel="self" type="application/rss+xml" /><item><title>Frugal Streaming for Estimating Quantiles:One (or two) memory suffices — mentioned by tadkar</title><link>https://news.ycombinator.com/item?id=25202448</link><guid isPermaLink="false">urn:hackerpapers:mention:1407.1121:25202448</guid><pubDate>Tue, 24 Nov 2020 20:05:23 GMT</pubDate><description>&lt;p&gt;Related to this, one of my favourite articles [1] suggests that it’s sufficient to only use one or two pieces of memory to get good estimates. Here’s a pretty amazing result from the paper. To estimate the median (loosely) on a stream, first set the median estimate m to 0 prior to seeing any data. Then as you observe the stream, increase the median estimate m by 1 if the current element s is bigger than m. Do nothing if the current element is the same as m. Decrease the estimate by 1 if the element is less than m. Then (given the right conditions) this process converges to the median. You can…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1407.1121/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.DB</category></item></channel></rss>
