<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Tutorial on Yu Xuan's Portfolio</title><link>https://yxlow07.github.io/tags/tutorial/</link><description>Recent content in Tutorial on Yu Xuan's Portfolio</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 10 May 2025 12:00:00 +0800</lastBuildDate><atom:link href="https://yxlow07.github.io/tags/tutorial/index.xml" rel="self" type="application/rss+xml"/><item><title>Getting Started with Dynamic Programming</title><link>https://yxlow07.github.io/blog/dynamic_programming/</link><pubDate>Sat, 10 May 2025 12:00:00 +0800</pubDate><guid>https://yxlow07.github.io/blog/dynamic_programming/</guid><description>Introduction to Dynamic Programming Dynamic programming is a powerful technique for solving complex problems by breaking them down into simpler subproblems. It&amp;rsquo;s particularly useful when the problem has overlapping subproblems and an optimal substructure.
Key Principles Optimal Substructure: The optimal solution to a problem contains optimal solutions to its subproblems. Overlapping Subproblems: The same subproblems are solved multiple times when finding the solution. Implementation Example: Fibonacci Sequence The Fibonacci sequence is a classic example of a problem that can be efficiently solved using dynamic programming:</description></item></channel></rss>