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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Discriminative Embeddings of Latent Variable Models for Structured Data · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1603.05629/</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/1603.05629/feed.xml" rel="self" type="application/rss+xml" /><item><title>Discriminative Embeddings of Latent Variable Models for Structured Data — mentioned by hoosieree</title><link>https://news.ycombinator.com/item?id=32083757</link><guid isPermaLink="false">urn:hackerpapers:mention:1603.05629:32083757</guid><pubDate>Wed, 13 Jul 2022 15:09:03 GMT</pubDate><description>&lt;p&gt;Yeah, I ended up creating new variables to get the compile to succeed. As for generating functions, I&amp;#x27;ll have to think about what that loss function would look like. I&amp;#x27;ve been looking at asm2vec[1] and structure2vec[2] for inspiration. I&amp;#x27;m currently looking at different kinds of graph embeddings, because even answering the basic question of &amp;quot;are these N bytes of assembly semantically similar to these other N bytes&amp;quot; is a challenge. [1]: https://ieeexplore.ieee.org/document/8835340 [2]: https://arxiv.org/abs/1603.05629&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1603.05629/"&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>
