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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Direct Feedback Alignment with Sparse Connections for Local Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1903.02083/</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/1903.02083/feed.xml" rel="self" type="application/rss+xml" /><item><title>Direct Feedback Alignment with Sparse Connections for Local Learning — mentioned by raindeer3</title><link>https://news.ycombinator.com/item?id=20666941</link><guid isPermaLink="false">urn:hackerpapers:mention:1903.02083:20666941</guid><pubDate>Sun, 11 Aug 2019 07:47:39 GMT</pubDate><description>&lt;p&gt;Very interesting also is that you can directly send the error to intermediate layers through sparse random projections without the need for any layerwise backpropagation. This relaxation of the structure of the backward pass makes bp even more plausible from a biological perspective. https://arxiv.org/abs/1609.01596 https://arxiv.org/abs/1903.02083&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1903.02083/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item></channel></rss>
