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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1510.00149/</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/1510.00149/feed.xml" rel="self" type="application/rss+xml" /><item><title>Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding — mentioned by cing</title><link>https://news.ycombinator.com/item?id=13172265</link><guid isPermaLink="false">urn:hackerpapers:mention:1510.00149:13172265</guid><pubDate>Tue, 13 Dec 2016 23:24:33 GMT</pubDate><description>&lt;p&gt;I believe several papers have examined efficiently pruning neural networks, but neural death would be better branding ;) (https://arxiv.org/pdf/1506.02626v3.pdf https://arxiv.org/pdf/1510.00149v5.pdf)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1510.00149/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding — mentioned by dharma1</title><link>https://news.ycombinator.com/item?id=10881992</link><guid isPermaLink="false">urn:hackerpapers:mention:1510.00149:10881992</guid><pubDate>Mon, 11 Jan 2016 18:09:24 GMT</pubDate><description>&lt;p&gt;Here&amp;#x27;s the paper - http://arxiv.org/pdf/1510.00149.pdf The compressed network achieves a decent speedup and energy saving on current hardware too (desktop/mobile) without significant loss of accuracy&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1510.00149/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
