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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1607.05368/</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/1607.05368/feed.xml" rel="self" type="application/rss+xml" /><item><title>An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation — mentioned by throwaway466453</title><link>https://news.ycombinator.com/item?id=14305742</link><guid isPermaLink="false">urn:hackerpapers:mention:1607.05368:14305742</guid><pubDate>Wed, 10 May 2017 03:37:28 GMT</pubDate><description>&lt;p&gt;&amp;gt; Google is usually the largest contributor to most ML conferences (NIPS, ICML, etc.) That is because of their overwhelming influence, not the quality of their publications. &amp;gt; They are rather straightforward to reimplement Le and Mikolov&amp;#x27;s &amp;quot;Distributed Representations of Sentences and Documents&amp;quot;, frequently cited as the original example of &amp;quot;doc2vec&amp;quot;, could not be reproduced by Mikolov himself. [1] &amp;gt; and I don&amp;#x27;t think anybody is accusing them of faking their results. They sure aren&amp;#x27;t. That, too, is because of their overwhelming influence. You have to say very nicely that their results are…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1607.05368/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
