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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1710.09553/</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/1710.09553/feed.xml" rel="self" type="application/rss+xml" /><item><title>Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior — mentioned by charleshmartin</title><link>https://news.ycombinator.com/item?id=18443503</link><guid isPermaLink="false">urn:hackerpapers:mention:1710.09553:18443503</guid><pubDate>Tue, 13 Nov 2018 18:39:30 GMT</pubDate><description>&lt;p&gt;I would say “Understanding Deep Learning Requires REMEMBERING Generalization” https://calculatedcontent.com/2018/04/01/rethinking-or-remem... https://arxiv.org/abs/1710.09553 We can understand this using the traditional theory of Statistical Mechanics of Generalization Briefly, shuffling the labels corresponds to decreasing the effective load on the Neural Network, which pushes the system into the spin glass phase&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1710.09553/"&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>
