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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AMLB: an AutoML Benchmark · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2207.12560/</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/2207.12560/feed.xml" rel="self" type="application/rss+xml" /><item><title>AMLB: an AutoML Benchmark — mentioned by newfocogi</title><link>https://news.ycombinator.com/item?id=37699054</link><guid isPermaLink="false">urn:hackerpapers:mention:2207.12560:37699054</guid><pubDate>Fri, 29 Sep 2023 03:45:38 GMT</pubDate><description>&lt;p&gt;I’m not sure how the authors can claim to be comparing their approach against “state of the art” AutoML and not include AutoGluon, FLAML or H2O. This independent benchmarking paper[0] is what the AutoML field points to as establishing SOTA, and the libraries compared against in the SapientML paper are middle of the pack at best. [0] https://arxiv.org/abs/2207.12560&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2207.12560/"&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>
