<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Information Theory | Rice Wireless</title><link>http://wireless.rice.edu/tags/information-theory/</link><atom:link href="http://wireless.rice.edu/tags/information-theory/index.xml" rel="self" type="application/rss+xml"/><description>Information Theory</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Tue, 05 May 2026 00:00:00 +0000</lastBuildDate><image><url>http://wireless.rice.edu/media/icon.svg</url><title>Information Theory</title><link>http://wireless.rice.edu/tags/information-theory/</link></image><item><title>Information Theory &amp; ML for Wireless</title><link>http://wireless.rice.edu/research/info-theory-ml/</link><pubDate>Tue, 05 May 2026 00:00:00 +0000</pubDate><guid>http://wireless.rice.edu/research/info-theory-ml/</guid><description>&lt;h2 id="overview"&gt;Overview&lt;/h2&gt;
&lt;p&gt;Our information-theoretic and machine-learning research provides the
foundations for next-generation wireless. Topics include distributed
network capacity, learning-based MIMO detection, ML-driven schedulers
and link adaptation, and AI for RF data understanding.&lt;/p&gt;</description></item></channel></rss>