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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2309.17130/</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/2309.17130/feed.xml" rel="self" type="application/rss+xml" /><item><title>GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data — mentioned by cgreerrun</title><link>https://news.ycombinator.com/item?id=38168445</link><guid isPermaLink="false">urn:hackerpapers:mention:2309.17130:38168445</guid><pubDate>Mon, 06 Nov 2023 20:24:29 GMT</pubDate><description>&lt;p&gt;You&amp;#x27;re welcome! If you&amp;#x27;re interested, there is a follow up paper about a method that extends GradTree to a boosted tree as well called GRANDE[1]. [1]https://arxiv.org/abs/2309.17130&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2309.17130/"&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>GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data — HN submission</title><link>https://news.ycombinator.com/item?id=37847563</link><guid isPermaLink="false">urn:hackerpapers:submission:2309.17130:37847563</guid><pubDate>Wed, 11 Oct 2023 17:32:38 GMT</pubDate><description>&lt;p&gt;Grande: Gradient-Based Decision Tree Ensembles&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;25 points; 1 discussion reply on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2309.17130/"&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>
