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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Verifiable evaluations of machine learning models using zkSNARKs · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2402.02675/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Thu, 05 Nov 2026 05:34:29 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2402.02675/feed.xml" rel="self" type="application/rss+xml" /><item><title>Verifiable evaluations of machine learning models using zkSNARKs — mentioned by fscaramuzza</title><link>https://news.ycombinator.com/item?id=50369882</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.02675:50369882</guid><pubDate>Wed, 04 Nov 2026 18:50:24 GMT</pubDate><description>&lt;p&gt;Well luckily not really, their work is more foundational-y, the idea is not new, but they made it more efficient and practical. On our side, we work more on the integration of these protocol in production systems, but we are pretty much on the frontier and is not very common to see such big companies experimenting with this technology. Microsoft already tried something [1] but I&amp;#x27;m not sure if it ever went further than a research prototype. [1] https://arxiv.org/pdf/2402.02675&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.02675/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
