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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Private Machine Learning in TensorFlow using Secure Computation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1810.08130/</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/1810.08130/feed.xml" rel="self" type="application/rss+xml" /><item><title>Private Machine Learning in TensorFlow using Secure Computation — mentioned by osaariki</title><link>https://news.ycombinator.com/item?id=21640346</link><guid isPermaLink="false">urn:hackerpapers:mention:1810.08130:21640346</guid><pubDate>Tue, 26 Nov 2019 17:20:03 GMT</pubDate><description>&lt;p&gt;TF Encrypted has focused more on MPC [1]. At least that&amp;#x27;s what their arXiv paper [2] talks about. It does seem they are also working to integrate Microsoft SEAL for HE. [1]: https://en.wikipedia.org/wiki/Secure_multi-party_computation [2]: https://arxiv.org/abs/1810.08130&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1810.08130/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CR</category></item><item><title>Private Machine Learning in TensorFlow using Secure Computation — HN submission</title><link>https://news.ycombinator.com/item?id=18256832</link><guid isPermaLink="false">urn:hackerpapers:submission:1810.08130:18256832</guid><pubDate>Fri, 19 Oct 2018 14:11:19 GMT</pubDate><description>&lt;p&gt;Private Machine Learning in TensorFlow Using Secure Computation&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;6 points; 1 discussion reply on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1810.08130/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CR</category></item></channel></rss>
