<?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>Decision-Making on The Standard Error</title><link>https://jongha-jeon-dev.github.io/standarderror/tags/decision-making/</link><description>Recent content in Decision-Making 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/decision-making/index.xml" rel="self" type="application/rss+xml"/><item><title>ML 50: A Rule That Chooses Its Own Data Learns Its Own Choices</title><link>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-50-feedback/</link><pubDate>Tue, 13 Oct 2026 00:00:00 +0000</pubDate><guid>https://jongha-jeon-dev.github.io/standarderror/lectures/ml-50-feedback/</guid><description>When a rule decides where to look and learns only from what it finds there, more data does not correct it. It has to account for its own effort, and keep looking where it expects nothing.</description></item></channel></rss>