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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>User-friendly introduction to PAC-Bayes bounds · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2110.11216/</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/2110.11216/feed.xml" rel="self" type="application/rss+xml" /><item><title>User-friendly introduction to PAC-Bayes bounds — mentioned by srean</title><link>https://news.ycombinator.com/item?id=49714960</link><guid isPermaLink="false">urn:hackerpapers:mention:2110.11216:49714960</guid><pubDate>Tue, 15 Sep 2026 16:27:16 GMT</pubDate><description>&lt;p&gt;You can try this one https://books.google.co.in/books/about/User_friendly_Introdu... Free download here https://arxiv.org/abs/2110.11216 One of the ICMLs had a nice tutorial by Langford and Banerjee on the relationship between the different style of bounds. 2003, I think.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2110.11216/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item></channel></rss>
