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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Tensor decompositions for learning latent variable models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1210.7559/</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/1210.7559/feed.xml" rel="self" type="application/rss+xml" /><item><title>Tensor decompositions for learning latent variable models — mentioned by boulos</title><link>https://news.ycombinator.com/item?id=32731535</link><guid isPermaLink="false">urn:hackerpapers:mention:1210.7559:32731535</guid><pubDate>Tue, 06 Sep 2022 01:25:55 GMT</pubDate><description>&lt;p&gt;It&amp;#x27;s too bad this article never links to the paper [1] being hinted at. In late 2012 (first submission) tensor decomposition was likely very interesting (the paper has &amp;gt;1000 citations!). But given that this article doesn&amp;#x27;t distinguish between &amp;quot;use tensors&amp;quot; and &amp;quot;use tensor decomposition, not SVD or similar for old school setups&amp;quot; I think the article is super confusing. Perhaps the author didn&amp;#x27;t get the distinction, and decided to write up a &amp;quot;renegade/rebel&amp;quot; piece that is sadly a non sequitur. [1] https://arxiv.org/abs/1210.7559&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1210.7559/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
