<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>混合计算 on PlumePHP</title><link>https://plumephp.com/tags/%E6%B7%B7%E5%90%88%E8%AE%A1%E7%AE%97/</link><description>Recent content in 混合计算 on PlumePHP</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Sun, 27 Sep 2026 10:00:00 +0800</lastBuildDate><atom:link href="https://plumephp.com/tags/%E6%B7%B7%E5%90%88%E8%AE%A1%E7%AE%97/index.xml" rel="self" type="application/rss+xml"/><item><title>量子机器学习入门：量子神经网络、量子核方法与混合量子经典</title><link>https://plumephp.com/quantum-machine-learning/</link><pubDate>Sun, 27 Sep 2026 10:00:00 +0800</pubDate><guid>https://plumephp.com/quantum-machine-learning/</guid><description>&lt;h2 id="引言"&gt;引言&lt;/h2&gt;
&lt;p&gt;机器学习靠数据与算力驱动，量子计算恰好提供一种全新的「算力」。量子机器学习（Quantum Machine Learning, QML）试图回答：能不能用量子系统的叠加与纠缠，加速或改善学习任务？这里面既有激动人心的可能，也有大量被夸大的炒作。&lt;/p&gt;</description></item></channel></rss>