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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Projective Clustering Product Quantization · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2112.02179/</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/2112.02179/feed.xml" rel="self" type="application/rss+xml" /><item><title>Projective Clustering Product Quantization — mentioned by gk1</title><link>https://news.ycombinator.com/item?id=29555279</link><guid isPermaLink="false">urn:hackerpapers:mention:2112.02179:29555279</guid><pubDate>Tue, 14 Dec 2021 18:29:11 GMT</pubDate><description>&lt;p&gt;It&amp;#x27;s great to see more and more talk of vector search and vector databases. We&amp;#x27;ve been promoting this technology for over a year now and have several intro articles for anyone looking to learn more[1], and a generous free tier on our vector search service[2] for anyone looking to give vector search a shot. [1] https://www.pinecone.io/learn/ [2] https://app.pinecone.io/ We are also actively researching the space, and just recently published a paper on improving Google&amp;#x27;s ScaNN: https://arxiv.org/abs/2112.02179&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2112.02179/"&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>
