Length of Longest Fibonacci Subsequence | Recursion Memo | Bottom Up |Leetcode 873| codestorywithMIK

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Published on February 27, 2025 4:52:07 AM ● Video Link: https://www.youtube.com/watch?v=Ut9cr6Ut4wY

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Hi Everyone, this is the 107th video of our Playlist "Dynamic Programming : Popular Interview Problems".
Now we will be solving a good Graph problem - Length of Longest Fibonacci Subsequence | Recursion | Memo | Bottom Up | Leetcode 873 | codestorywithMIK

We will start from a beginner's point of view. Build our solution from a simple Recursion and then move to Memoization and then finally to Bottom Up

Problem Name : Length of Longest Fibonacci Subsequence | Recursion | Memo | Bottom Up | Leetcode 873 | codestorywithMIK
Company Tags : will update later
My solutions on Github(C++ & JAVA) - https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/DP/Length of Longest Fibonacci Subsequence.cpp
Leetcode Link : https://leetcode.com/problems/length-of-longest-fibonacci-subsequence


My DP Concepts Playlist :    • Roadmap for DP | How to Start DP ? | ...  
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Video Summary :
Approach-1 (Recursion + Memoization)
This approach explores all possible Fibonacci-like subsequences using recursion. For each pair (j, k), it checks if a valid previous element exists and recursively finds the longest sequence ending at (j, k). Memoization is used to store results and avoid redundant calculations.

Approach-2 (Bottom-Up)
This approach builds the solution iteratively using a 2D table t[j][k], where each entry stores the longest subsequence ending at (j, k). By iterating over all possible pairs and looking up previous elements efficiently, it constructs the solution in a structured manner.


✨ Timelines✨
00:00 - Introduction
0:39 - Motivation
1:25 - Problem Explanation
5:44 - Thought Process Beginner POV
13:49 - Story To Code
24:41 - Simple Dry Run
28:55 - Time & Space Complexity
30:17 - Coding Recursion
33:52 - Why Memoization
37:02 - Coding Memoization
38:55 - Understand Bottom Up Easily
45:50 - Time & Space Complexity
46:09 - Coding Bottom Up

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