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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Latent Multi-task Architecture Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1705.08142/</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/1705.08142/feed.xml" rel="self" type="application/rss+xml" /><item><title>Latent Multi-task Architecture Learning — mentioned by syllogism</title><link>https://news.ycombinator.com/item?id=14854990</link><guid isPermaLink="false">urn:hackerpapers:mention:1705.08142:14854990</guid><pubDate>Wed, 26 Jul 2017 10:25:16 GMT</pubDate><description>&lt;p&gt;(I&amp;#x27;m the lead author of spaCy) spaCy 2 is reconfigured for deep learning. It&amp;#x27;s still in alpha, but there&amp;#x27;s already a lot there: http://alpha.spacy.io/docs/ I wrote a whole neural network library to get this done, because Tensorflow and Theano are terrible for the type of models NLP needs. Joke was sort of on me, because PyTorch came out just as I was finishing :). But it&amp;#x27;s actually very good to own the dependencies of the library anyway, since it&amp;#x27;s such an important part of things. Having our own NN library has made it easy to make lots of small innovations along the way. The best one is…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1705.08142/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item></channel></rss>
