<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Learning Combinatorial Optimization Algorithms over Graphs · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1704.01665/</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/1704.01665/feed.xml" rel="self" type="application/rss+xml" /><item><title>Learning Combinatorial Optimization Algorithms over Graphs — mentioned by _raoulcousins</title><link>https://news.ycombinator.com/item?id=17396161</link><guid isPermaLink="false">urn:hackerpapers:mention:1704.01665:17396161</guid><pubDate>Mon, 25 Jun 2018 21:55:36 GMT</pubDate><description>&lt;p&gt;Absolutely. People are using ML for plenty of difficult problems. In operations research, a lot of time is spent coming up with heuristic solutions to hard optimization problems. This problem is plenty hard for people to do. There has been some recent work in using ML to create solution methods, like the paper Learning Combinatorial Optimization Algorithms over Graphs (https://arxiv.org/abs/1704.01665).&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1704.01665/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Learning Combinatorial Optimization Algorithms over Graphs — HN submission</title><link>https://news.ycombinator.com/item?id=15870368</link><guid isPermaLink="false">urn:hackerpapers:submission:1704.01665:15870368</guid><pubDate>Thu, 07 Dec 2017 14:48:02 GMT</pubDate><description>&lt;p&gt;Learning Combinatorial Optimization Algorithms Over Graphs&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;88 points; 1 discussion reply on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1704.01665/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
