<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>E. C. C. Tsang | Trustworthy AI Systems Lab (TAS Lab)</title><link>https://tas-lab.org/author/e.-c.-c.-tsang/</link><atom:link href="https://tas-lab.org/author/e.-c.-c.-tsang/index.xml" rel="self" type="application/rss+xml"/><description>E. C. C. Tsang</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Fri, 01 Jan 2021 00:00:00 +0000</lastBuildDate><image><url>https://tas-lab.org/media/icon_hu_9cf092d4d003c2c7.png</url><title>E. C. C. Tsang</title><link>https://tas-lab.org/author/e.-c.-c.-tsang/</link></image><item><title>Robustness analysis of classical and fuzzy decision trees under adversarial evasion attack</title><link>https://tas-lab.org/publication/2021-robustness-classical-fuzzy-decision-trees/</link><pubDate>Fri, 01 Jan 2021 00:00:00 +0000</pubDate><guid>https://tas-lab.org/publication/2021-robustness-classical-fuzzy-decision-trees/</guid><description/></item></channel></rss>