<?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>数学 on Blog</title><link>https://icelemon.top/tags/%E6%95%B0%E5%AD%A6/</link><description>Recent content in 数学 on Blog</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Mon, 19 Oct 2026 00:00:00 +0800</lastBuildDate><atom:link href="https://icelemon.top/tags/%E6%95%B0%E5%AD%A6/index.xml" rel="self" type="application/rss+xml"/><item><title>37% 法则，究竟在什么条件下最优</title><link>https://icelemon.top/knowledge/secretary-problem/</link><pubDate>Mon, 19 Oct 2026 00:00:00 +0800</pubDate><guid>https://icelemon.top/knowledge/secretary-problem/</guid><description>先观察，再选择：秘书问题的解法，以及它能够回答的问题。</description></item><item><title>从一片噪声，到一张图像</title><link>https://icelemon.top/knowledge/diffusion-models/</link><pubDate>Mon, 19 Oct 2026 00:00:00 +0800</pubDate><guid>https://icelemon.top/knowledge/diffusion-models/</guid><description>扩散模型怎样把生成图像，拆成一连串可以学习的去噪任务。</description></item><item><title>信息有多少，取决于原来有多不确定</title><link>https://icelemon.top/knowledge/information-and-surprise/</link><pubDate>Mon, 19 Oct 2026 00:00:00 +0800</pubDate><guid>https://icelemon.top/knowledge/information-and-surprise/</guid><description>从猜数到深空通信，理解比特、信息熵、压缩与纠错。</description></item></channel></rss>