<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Online Learning on 中文AI术语词典</title><link>https://terms-en.ai-term-hub.com/zh/tags/online-learning/</link><description>Recent content in Online Learning on 中文AI术语词典</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Sat, 18 Jul 2026 11:44:45 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/zh/tags/online-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>乘法权重更新法</title><link>https://terms-en.ai-term-hub.com/zh/terms/multiplicative_weight_update_method/</link><pubDate>Sat, 18 Jul 2026 11:27:47 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/zh/terms/multiplicative_weight_update_method/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>乘法权重更新法是一种基础的在线学习算法，用于在不确定环境中做出决策。它为不同的策略或专家维护一组权重，并根据其表现动态调整这些权重，从而优化长期决策效果。&lt;/p>
&lt;h3 id="summary">Summary&lt;/h3>
&lt;p>一种迭代算法，根据性能反馈以乘法方式更新权重，以最小化遗憾值。&lt;/p>
&lt;h2 id="key-concepts">Key Concepts&lt;/h2>
&lt;ul>
&lt;li>在线学习&lt;/li>
&lt;li>加权多数算法&lt;/li>
&lt;li>遗憾最小化&lt;/li>
&lt;li>指数加权&lt;/li>
&lt;/ul>
&lt;h2 id="use-cases">Use Cases&lt;/h2>
&lt;ul>
&lt;li>投资组合优化&lt;/li>
&lt;li>专家建议聚合&lt;/li>
&lt;li>对抗性老虎机问题&lt;/li>
&lt;/ul>
&lt;h2 id="related-terms">Related Terms&lt;/h2>
&lt;ul>
&lt;li>&lt;a href="https://terms-en.ai-term-hub.com/en/terms/gradient_descent-%E6%A2%AF%E5%BA%A6%E4%B8%8B%E9%99%8D/">gradient_descent (梯度下降)&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://terms-en.ai-term-hub.com/en/terms/online_learning-%E5%9C%A8%E7%BA%BF%E5%AD%A6%E4%B9%A0/">online_learning (在线学习)&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://terms-en.ai-term-hub.com/en/terms/regret_bound-%E9%81%97%E6%86%BE%E7%95%8C/">regret_bound (遗憾界)&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://terms-en.ai-term-hub.com/en/terms/boosting-%E6%8F%90%E5%8D%87%E7%AE%97%E6%B3%95/">boosting (提升算法)&lt;/a>&lt;/li>
&lt;/ul></description></item></channel></rss>