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Maximum Subarray Problem using Kadane’s Algorithm in just minutes!
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Maximum Subarray Problem using Kadane’s Algorithm in just minutes!
Maximum Subarray Problem using Kadane’s Algorithm in just minutes! Learn how current_sum and max_sum help track the best subarray and understand the clean intuition behind it. Perfect for coding interviews, LeetCode prep, and DSA beginners. 🔥 Save this for revision 🔥 Share with your coding friends 🔥 Follow for more fast DSA ...
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Dynamic Programming Algorithms
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Consider a divide and conquer algorithm which takes an input set P with |P| = n and divides it into two pieces, P1 and P2. The two pieces are such that P1 ∩ P2 = φ, P1 ∪ P2 = P, and |P1| ≥ (n/3) and |P2| ≥ (n/3). The algorithm recursively solves the problem on P1 and P2 and merges the solution in O(n^1.5) time. In the base case, when the problem is of size 1, the algorithm returns the correct solution in 1 step. Show that the running time of this algorithm is O(n^1.5). You will still re
Consider a divide and conquer algorithm which takes an input set P with |P| = n and divides it into two pieces, P1 and P2. The two pieces are such that P1 ∩ P2 = φ, P1 ∪ P2 = P, and |P1| ≥ (n/3) and |P2| ≥ (n/3). The algorithm recursively solves the problem on P1 and P2 and merges the solution in O(n^1.5) time. In the base case, when the problem is of size 1, the algorithm returns the correct solution in 1 step. Show that the running time of this algorithm is O(n^1.5). You will still re
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