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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Fuzzy Bayesian Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1610.09156/</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/1610.09156/feed.xml" rel="self" type="application/rss+xml" /><item><title>Fuzzy Bayesian Learning — mentioned by nextaccountic</title><link>https://news.ycombinator.com/item?id=25175662</link><guid isPermaLink="false">urn:hackerpapers:mention:1610.09156:25175662</guid><pubDate>Sun, 22 Nov 2020 07:20:31 GMT</pubDate><description>&lt;p&gt;That&amp;#x27;s fascinating! &amp;gt; This type of uncertainty is better addressed using fuzzy measures other than probability (which is only a subset of more general fuzzy theory). Do you mean that both probability theory and possibility theory are subsumed by fuzzy logic? What about works that integrate fuzzy logic and probability? eg. https://arxiv.org/abs/1610.09156 employs both fuzzy logic and probability; can those be understood in terms of fuzzy logic alone? &amp;gt; See Klir &amp;amp; Folger for nice discussion on this (I forget the title, but it is called something like Uncertainty in Fuzzy Theory Applications).…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1610.09156/"&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>
