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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Quantum advantage for learning shallow neural networks with natural data distributions · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2503.20879/</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/2503.20879/feed.xml" rel="self" type="application/rss+xml" /><item><title>Quantum advantage for learning shallow neural networks with natural data distributions — mentioned by westurner</title><link>https://news.ycombinator.com/item?id=43537715</link><guid isPermaLink="false">urn:hackerpapers:mention:2503.20879:43537715</guid><pubDate>Mon, 31 Mar 2025 17:48:58 GMT</pubDate><description>&lt;p&gt;ScholarlyArticle: &amp;quot;Quantum advantage for learning shallow neural networks with natural data distributions&amp;quot; (2025) https://arxiv.org/abs/2503.20879 NewsArticle: &amp;quot;Google Researchers Say Quantum Theory Suggests a Shortcut for Learning Certain Neural Networks&amp;quot; (2025) https://thequantuminsider.com/2025/03/31/google-researchers-... : &amp;gt; Using this model, [Quantum Statistical Query (QSQ) learning,] the authors design a two-part algorithm. First, the quantum algorithm finds the hidden period in the function using a modified form of quantum Fourier transform — a core capability of quantum computers.…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2503.20879/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>quant-ph</category></item><item><title>Quantum advantage for learning shallow neural networks with natural data distributions — HN submission</title><link>https://news.ycombinator.com/item?id=43537640</link><guid isPermaLink="false">urn:hackerpapers:submission:2503.20879:43537640</guid><pubDate>Mon, 31 Mar 2025 17:42:27 GMT</pubDate><description>&lt;p&gt;Quantum advantage for learning shallow NNs with natural data distributions&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2503.20879/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>quant-ph</category></item></channel></rss>
