<?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>Extrapolation on The Standard Error</title><link>https://jongha-jeon-dev.github.io/standarderror/tags/extrapolation/</link><description>Recent content in Extrapolation on The Standard Error</description><generator>Hugo -- 0.123.7</generator><language>en-gb</language><lastBuildDate>Tue, 13 Oct 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://jongha-jeon-dev.github.io/standarderror/tags/extrapolation/index.xml" rel="self" type="application/rss+xml"/><item><title>ML 15: A Forest Cannot Predict Beyond the Largest Value It Has Seen</title><link>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-15-extrapolation/</link><pubDate>Mon, 12 Oct 2026 00:00:00 +0000</pubDate><guid>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-15-extrapolation/</guid><description>Tree ensembles are said to approximate any function. Inside the training range they do; outside it their predictions go flat, below the largest label they saw, and the best single model becomes the worst.</description></item><item><title>ML 30: A Power Law Fitted on Small Models Cannot See the Floor</title><link>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-30-scaling/</link><pubDate>Tue, 13 Oct 2026 00:00:00 +0000</pubDate><guid>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-30-scaling/</guid><description>Eight character transformers, one budget of data and steps. The law fitted to the five smallest predicts the next size almost exactly and the largest too optimistically.</description></item></channel></rss>