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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine Learning at Microsoft with ML .NET · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1905.05715/</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/1905.05715/feed.xml" rel="self" type="application/rss+xml" /><item><title>Machine Learning at Microsoft with ML .NET — HN submission</title><link>https://news.ycombinator.com/item?id=42969204</link><guid isPermaLink="false">urn:hackerpapers:submission:1905.05715:42969204</guid><pubDate>Fri, 07 Feb 2025 03:57:38 GMT</pubDate><description>&lt;p&gt;Ml.net&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1905.05715/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Machine Learning at Microsoft with ML .NET — HN submission</title><link>https://news.ycombinator.com/item?id=20632487</link><guid isPermaLink="false">urn:hackerpapers:submission:1905.05715:20632487</guid><pubDate>Wed, 07 Aug 2019 06:50:36 GMT</pubDate><description>&lt;p&gt;Machine Learning at Microsoft with ML.net&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1905.05715/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Machine Learning at Microsoft with ML .NET — mentioned by TheIronYuppie</title><link>https://news.ycombinator.com/item?id=20501814</link><guid isPermaLink="false">urn:hackerpapers:mention:1905.05715:20501814</guid><pubDate>Mon, 22 Jul 2019 20:07:15 GMT</pubDate><description>&lt;p&gt;For what it&amp;#x27;s worth, we are pretty proud of the performance as well - I wouldn&amp;#x27;t call it training wheels :) On both scale up and run times, it measures up as among the best-in-class[1]. That is to say, for the scenarios which people use it most commonly (GBT, linear learners), it&amp;#x27;s a great fit! [1] https://arxiv.org/pdf/1905.05715.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1905.05715/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Machine Learning at Microsoft with ML .NET — HN submission</title><link>https://news.ycombinator.com/item?id=19918746</link><guid isPermaLink="false">urn:hackerpapers:submission:1905.05715:19918746</guid><pubDate>Wed, 15 May 2019 12:34:16 GMT</pubDate><description>&lt;p&gt;Machine Learning at Microsoft with ML.NET&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1905.05715/"&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>
