Maximum Sum Rectangle In A 2D Matrix? Top Answer Update


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1. Shares. Given a 2D array, find the maximum sum subarray in it. For example, in the following 2D array, the maximum sum subarray is highlighted with blue rectangle and sum of this subarray is 29. This problem is mainly an extension of Largest Sum Contiguous Subarray for 1D array. The naive solution for this problem is to check every possible.


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Maximum sum Rectangle Try It! The Naive Solution for this problem is to check every possible rectangle in the given 2D array. This solution requires 6 nested loops - 4 for start and end coordinate of the 2 axis O (n4) and 2 for the summation of the sub-matrix O (n2). Below is the implementation of the above approach: C++ Java Python3 C# Javascript


Maximum Sum Rectangle In A 2D Matrix? Top Answer Update

C Program for Maximum sum rectangle in a 2D matrix using Naive Approach: The Naive Solution for this problem is to check every possible rectangle in the given 2D array. This solution requires 6 nested loops - 4 for start and end coordinate of the 2 axis O (n4) and 2 for the summation of the sub-matrix O (n2).


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Maximum sum rectangle in a 2D matrix Data Structure Dynamic Programming Algorithms A matrix is given. We need to find a rectangle (sometimes square) matrix, whose sum is maximum.


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Explanation 1: We can observe from the image that the shaded submatrix denotes the maximum sum rectangle in the above example. The sum of elements in this submatrix gives us a value of 29. Input 2: Matrix = { {1, 0, 1, 0, 1}, {0, 1, 0, 1, 0}, {1, 0, 1, 0, 1}, {0, 1, 0, 1, 0}} Output 2: (top, left) : (0, 0) (bottom, right) : (3, 4) 10


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Given a 2D array, find the maximum sum subarray in it. For example, in the following 2D array, the maximum sum subarray is highlighted with blue rectangle and sum of this subarray is 29. This problem is mainly an extension of Largest Sum Contiguous Subarray for 1D array .


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Minimax Powered By GitBook Maximum Sum Rectangle in a 2D Matrix Given a 2D array, find the maximum sum subarray in it. For example, in the following 2D array, the maximum sum subarray is highlighted with blue rectangle and sum of this subarray is 29. Source: https://www.geeksforgeeks.org/maximum-sum-rectangle-in-a-2d-matrix-dp-27/


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Given a 2D matrix M of dimensions RxC. Find the maximum sum submatrix in it. Example 1: Input: R=4 C=5 M= [ [1,2,-1,-4,-20], [-8,-3,4,2,1], [3,8,10,1,3], [-4,-1,1,7,-6]] Output: 29 Explanation: The matrix is as follows and the blue r


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GFG link : https://www.geeksforgeeks.org/maximum-sum-rectangle-in-a-2d-matrix-dp-27/Code :https://github.com/anuragzv1/Youtube-Tutorials/blob/master/MaxRecta.


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Maximum sum rectangle in a 2D matrix Solution Basic Solution. The basic approach is to iterate over all rectangles. Since we are dealing with a 2-D matrix we require 4 loops to iterate and 2 loops to find sum. Thus the time complexity of this approach is O((r^3)*(c^3)).


Programming Interview 23 Find the maximum sum of a submatrix in a 2D

We can find the maximum sum submatrix in given matrix by using a naive solution. We can use four nested loops each for different indices. So, one will be for starting row index, starting column index, ending row index, and ending column index.


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#dp #competitiveprogramming #coding #dsa #dynamicprogramming Hey Guys in this video I have explained with code how we can solve the problem 'Maximum sum rectangle in a 2D matrix'..more.more


Max sum rectangle in 2D Matrix Optimal Approach Solution + Code

I write this code for Maximum sum rectangle in a 2D matrix problem. But it return false answer. For example for this instance return 0 while the correct answer is 15. User first give size of array then enter elements. What is my mistake? Example 0 -2 -7 0 9 2 -6 2 -4 1 -4 1 -1 8 0 -2 Code


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Maximum sum rectangle in a 2D matrix using divide and conquer Ask Question Asked 2 years, 3 months ago Modified 2 years, 3 months ago Viewed 931 times 2 I need to implement a maximum sum algorithm that uses the divide and conquer strategy on a 2D matrix.


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Maximum Sum Rectangle In A 2D Matrix? Top Answer Update

When values in the matrix are all positive the answer is pretty straight forward, the maximum sum rectangle is the matrix itself. We use dynamic programming to reduce the brute force time complexity to O (N^3). The idea is to fix the left and right columns one by one and find the maximum sum contiguous rows for every left and right column pair.