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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Bayesian Optimization for Machine Learning : A Practical Guidebook · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1612.04858/</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/1612.04858/feed.xml" rel="self" type="application/rss+xml" /><item><title>Bayesian Optimization for Machine Learning : A Practical Guidebook — HN submission</title><link>https://news.ycombinator.com/item?id=13192558</link><guid isPermaLink="false">urn:hackerpapers:submission:1612.04858:13192558</guid><pubDate>Fri, 16 Dec 2016 11:36:55 GMT</pubDate><description>&lt;p&gt;Bayesian Optimization for Machine Learning – Dewancker, McCourt, Clark&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;3 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1612.04858/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
