<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>优化器 on caulif的个人博客</title><link>https://www.caulif.com/tags/%E4%BC%98%E5%8C%96%E5%99%A8/</link><description>Recent content in 优化器 on caulif的个人博客</description><generator>Hugo -- 0.154.5</generator><language>zh-cn</language><lastBuildDate>Fri, 26 Jun 2026 00:00:00 +0800</lastBuildDate><atom:link href="https://www.caulif.com/tags/%E4%BC%98%E5%8C%96%E5%99%A8/index.xml" rel="self" type="application/rss+xml"/><item><title>反向传播（Backpropagation）学习笔记</title><link>https://www.caulif.com/posts/%E5%8F%8D%E5%90%91%E4%BC%A0%E6%92%AD%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0/</link><pubDate>Fri, 26 Jun 2026 00:00:00 +0800</pubDate><guid>https://www.caulif.com/posts/%E5%8F%8D%E5%90%91%E4%BC%A0%E6%92%AD%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0/</guid><description>整理反向传播的 Loss、梯度、链式法则、优化器更新，以及 LLM 训练中常见的显存优化方法。</description></item></channel></rss>