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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>The Modern Mathematics of Deep Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2105.04026/</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/2105.04026/feed.xml" rel="self" type="application/rss+xml" /><item><title>The Modern Mathematics of Deep Learning — HN submission</title><link>https://news.ycombinator.com/item?id=36361545</link><guid isPermaLink="false">urn:hackerpapers:submission:2105.04026:36361545</guid><pubDate>Fri, 16 Jun 2023 18:34:27 GMT</pubDate><description>&lt;p&gt;The Modern Mathematics of Deep Learning&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/2105.04026/"&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>The Modern Mathematics of Deep Learning — mentioned by sinenomine</title><link>https://news.ycombinator.com/item?id=34319044</link><guid isPermaLink="false">urn:hackerpapers:mention:2105.04026:34319044</guid><pubDate>Tue, 10 Jan 2023 01:22:27 GMT</pubDate><description>&lt;p&gt;Ironic, since the relatively recently discovered double descent makes it clear that bias-variance tradeoff as we know it from statistical learning theory simply doesn&amp;#x27;t apply to &amp;quot;overparameterized&amp;quot; deep models. Much of old theory is barely applicable and people are, understandably, bewildered and in denial. If someone were to be inclined to theory, I&amp;#x27;d just recommend reading papers that don&amp;#x27;t try oversimplify the domain: https://arxiv.org/abs/2006.15191 https://arxiv.org/abs/2210.10749 https://arxiv.org/abs/2205.10343 https://arxiv.org/abs/2105.04026&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2105.04026/"&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>The Modern Mathematics of Deep Learning — HN submission</title><link>https://news.ycombinator.com/item?id=27485574</link><guid isPermaLink="false">urn:hackerpapers:submission:2105.04026:27485574</guid><pubDate>Sat, 12 Jun 2021 16:37:55 GMT</pubDate><description>&lt;p&gt;The Modern Mathematics of Deep Learning&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;276 points; 70 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2105.04026/"&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>The Modern Mathematics of Deep Learning — HN submission</title><link>https://news.ycombinator.com/item?id=27474382</link><guid isPermaLink="false">urn:hackerpapers:submission:2105.04026:27474382</guid><pubDate>Fri, 11 Jun 2021 15:06:38 GMT</pubDate><description>&lt;p&gt;The Modern Mathematics of Deep Learning&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;23 points; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2105.04026/"&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>The Modern Mathematics of Deep Learning — HN submission</title><link>https://news.ycombinator.com/item?id=27129288</link><guid isPermaLink="false">urn:hackerpapers:submission:2105.04026:27129288</guid><pubDate>Wed, 12 May 2021 12:02:35 GMT</pubDate><description>&lt;p&gt;The modern mathematics of deep learning&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/2105.04026/"&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>
