<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Feature Purification: How Adversarial Training Performs Robust Deep Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2005.10190/</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/2005.10190/feed.xml" rel="self" type="application/rss+xml" /><item><title>Feature Purification: How Adversarial Training Performs Robust Deep Learning — mentioned by MindGods</title><link>https://news.ycombinator.com/item?id=23691630</link><guid isPermaLink="false">urn:hackerpapers:mention:2005.10190:23691630</guid><pubDate>Tue, 30 Jun 2020 16:17:40 GMT</pubDate><description>&lt;p&gt;Paper: &amp;quot;Feature Purification: How Adversarial Training Performs Robust Deep Learning&amp;quot; https://arxiv.org/abs/2005.10190&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2005.10190/"&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>
