(CS 577) Lecture 4a: Maximum Sum Subarray
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YouTubeJeremy McMahan
(CS 577) Lecture 4a: Maximum Sum Subarray
Lecture 4a from CS 577: Introduction to Algorithms, originally presented at the University of Wisconsin-Madison's Summer 2022 Semester. Lecture was developed and presented by Jeremy McMahan. This guided problem solving supplementary lecture presents the idea of computing maximum sum subarrays using dynamic programming.
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Maximum Subarray Sum Algorithm
SOLVED: Convert the pseudocode into a C functionThe Maximum Subarray ProblemThe maximum subarray problem involves finding a contiguous part of an array of numbers that adds up to the greatest possible sum.Maximum subarray problem input: a non-empty vector V of n integersOutput: indices b, e such that 0 ≤ b sum(v[b:e]): b = i e = j return (b, e)The two nested loops together iterate O(n^2) times, and the sum operation takes O(n) time, so the total time comp
SOLVED: Convert the pseudocode into a C functionThe Maximum Subarray ProblemThe maximum subarray problem involves finding a contiguous part of an array of numbers that adds up to the greatest possible sum.Maximum subarray problem input: a non-empty vector V of n integersOutput: indices b, e such that 0 ≤ b sum(v[b:e]): b = i e = j return (b, e)The two nested loops together iterate O(n^2) times, and the sum operation takes O(n) time, so the total time comp
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