The Find the Sum of Subsequence Powers interview question is a complex combinatorial optimization challenge. You are given an array of integers and an integer k. You need to find all subsequences of length k, calculate the "power" of each subsequence (defined as the minimum absolute difference between any two elements in that subsequence), and return the sum of all these powers.
Companies like Google and Rubrik ask the Find the Sum of Subsequence Powers coding problem to test a candidate's mastery of Dynamic Programming and Sorting. It is a "Hard" problem because the number of subsequences is exponential. It evaluations your ability to use DP to count subsequences that satisfy a specific minimum-difference property.
This problem is solved using Sorting and Dynamic Programming.
dp[i][j][diff] represents the number of subsequences of length j ending at index i with a minimum difference of exactly diff.diff can be large, it's often easier to define dp[i][j][target_diff] as the count of subsequences with min diff .nums = [1, 2, 3, 4], k = 3.
Subsequences of length 3:
[1, 2, 3]: Min diff 1.[1, 2, 4]: Min diff 1.[1, 3, 4]: Min diff 1.[2, 3, 4]: Min diff 1.
Sum of powers: .diff values to check.Master the "Counting Subsequences" DP pattern. If a problem asks for properties of all subsequences, look for a way to build them incrementally. Sorting is almost always the first step for problems involving absolute differences or ranges in Dynamic Programming interview patterns.
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