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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Memcomputing for Accelerated Optimization · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2003.10644/</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/2003.10644/feed.xml" rel="self" type="application/rss+xml" /><item><title>Memcomputing for Accelerated Optimization — mentioned by thxg</title><link>https://news.ycombinator.com/item?id=35909453</link><guid isPermaLink="false">urn:hackerpapers:mention:2003.10644:35909453</guid><pubDate>Thu, 11 May 2023 22:56:22 GMT</pubDate><description>&lt;p&gt;MemComputing mainly present themselves as optimizers: Their machine can solve real optimization problems, in practice, today. This is very good because, through that lens, we can skip the BS and go straight to the facts. The evaluation criteria for any optimization approach/algorithm are: - the quality of the solutions found (in the best case: optimal solutions) - the presence or absence of optimality guarantees (for example, some algorithms provide optimal solutions very often, but cannot guarantee it 100%) - the time (or computational cost) needed to find such solutions Furthermore, the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2003.10644/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.ET</category></item></channel></rss>
