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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1503.01057/</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/1503.01057/feed.xml" rel="self" type="application/rss+xml" /><item><title>Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) — mentioned by vladf</title><link>https://news.ycombinator.com/item?id=33820217</link><guid isPermaLink="false">urn:hackerpapers:mention:1503.01057:33820217</guid><pubDate>Thu, 01 Dec 2022 18:16:45 GMT</pubDate><description>&lt;p&gt;GPs over time series can leverage low-dimensional index sets for O(N lg N) fitting and inference. This can be done by interpolating the inputs onto a regular grid which admits Toeplitz kernels. See https://arxiv.org/abs/1503.01057.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1503.01057/"&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>
