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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Connecting Generative Adversarial Networks and Actor-Critic Methods · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1610.01945/</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/1610.01945/feed.xml" rel="self" type="application/rss+xml" /><item><title>Connecting Generative Adversarial Networks and Actor-Critic Methods — mentioned by gwern</title><link>https://news.ycombinator.com/item?id=16693357</link><guid isPermaLink="false">urn:hackerpapers:mention:1610.01945:16693357</guid><pubDate>Tue, 27 Mar 2018 22:26:15 GMT</pubDate><description>&lt;p&gt;Depends on whether you see the glass half-full or half-empty. Is it a DRL actor-critic where the reward &amp;amp; critic happen to be half of a GAN, or is it a GAN where the generator happens to receive a RL-style loss instead of the normal discriminator loss? Actor-critic and GANs have always been hard to tell apart: https://arxiv.org/pdf/1610.01945.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1610.01945/"&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>
