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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1906.02107/</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/1906.02107/feed.xml" rel="self" type="application/rss+xml" /><item><title>Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization — mentioned by concurrentsquar</title><link>https://news.ycombinator.com/item?id=39888458</link><guid isPermaLink="false">urn:hackerpapers:mention:1906.02107:39888458</guid><pubDate>Sun, 31 Mar 2024 22:01:06 GMT</pubDate><description>&lt;p&gt;You don&amp;#x27;t (you have to use real-valued inertial &amp;#x27;latent weights&amp;#x27; during training): https://arxiv.org/abs/1906.02107 (there is still a reduction in memory usage though (just not 24x): &amp;gt; &amp;quot;Furthermore, Bop reduces the memory requirements during training: it requires only one real-valued variable per weight, while the latent-variable approach with Momentum and Adam require two and three respectively.&amp;quot;)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1906.02107/"&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>
