<?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>Linear-Algebra on HJJJ的个人小站</title><link>https://hjjj.top/categories/linear-algebra/</link><description>Recent content in Linear-Algebra on HJJJ的个人小站</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 04 Aug 2026 00:00:00 +0800</lastBuildDate><atom:link href="https://hjjj.top/categories/linear-algebra/index.xml" rel="self" type="application/rss+xml"/><item><title>线性代数基础（一）：向量与空间</title><link>https://hjjj.top/posts/computer-science/linear-algebra/vectors-and-spaces/</link><pubDate>Tue, 04 Aug 2026 00:00:00 +0800</pubDate><guid>https://hjjj.top/posts/computer-science/linear-algebra/vectors-and-spaces/</guid><description>从几何直觉到线性无关与基：看懂 Jacobian 与相似度计算的向量基础</description></item><item><title>线性代数基础（二）：矩阵与线性变换</title><link>https://hjjj.top/posts/computer-science/linear-algebra/matrices-and-linear-transformations/</link><pubDate>Tue, 04 Aug 2026 00:00:00 +0900</pubDate><guid>https://hjjj.top/posts/computer-science/linear-algebra/matrices-and-linear-transformations/</guid><description>矩阵乘法、逆与行列式：看懂神经网络 Wx+b 与 Jacobian 的矩阵形式</description></item><item><title>线性代数基础（三）：特征值与分解</title><link>https://hjjj.top/posts/computer-science/linear-algebra/eigenvalues-and-decompositions/</link><pubDate>Tue, 04 Aug 2026 00:00:00 +1000</pubDate><guid>https://hjjj.top/posts/computer-science/linear-algebra/eigenvalues-and-decompositions/</guid><description>特征值、对角化与 SVD：看懂梯度消失与低秩近似的谱视角</description></item><item><title>线性代数进阶：矩阵微积分如何服务反向传播</title><link>https://hjjj.top/posts/computer-science/linear-algebra/matrix-calculus-for-backprop/</link><pubDate>Sat, 01 Aug 2026 00:00:00 +0800</pubDate><guid>https://hjjj.top/posts/computer-science/linear-algebra/matrix-calculus-for-backprop/</guid><description>不重复基础线性代数，只解释 Jacobian、向量-Jacobian 乘积和深度网络中的链式法则</description></item></channel></rss>