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The maximum subarray problem was proposed by Ulf Grenander in 1977 as a simplified model for maximum likelihood estimation of patterns in digitized images. [5]Grenander was looking to find a rectangular subarray with maximum sum, in a two-dimensional array of real numbers.
The maximum sum is 1, attained by giving one agent the item with value 1 and the other agent nothing. But the max-min allocation gives each agent value at least e, so the sum must be at most 3e. Therefore the POF is 1/(3e), which is unbounded. Alice has two items with values 1 and e, for some small e>0. George has two items with value e. The ...
This algorithm is an improvement over previously known quadratic time algorithms. [1] The maximum scoring subsequence from the set produced by the algorithm is also a solution to the maximum subarray problem. The Ruzzo–Tompa algorithm has applications in bioinformatics, [4] web scraping, [5] and information retrieval. [6]
Sum of sets The Minkowski sum of two sets A {\displaystyle A} and B {\displaystyle B} of real numbers is the set A + B := { a + b : a ∈ A , b ∈ B } {\displaystyle A+B~:=~\{a+b:a\in A,b\in B\}} consisting of all possible arithmetic sums of pairs of numbers, one from each set.
The subset sum problem (SSP) is a decision problem in computer science. In its most general formulation, there is a multiset of integers and a target-sum , and the question is to decide whether any subset of the integers sum to precisely . [1] The problem is known to be NP-complete.
Each possible sub-array is represented by a point on a colored line. That point's y-coordinate represents the sum of the sample, its x-coordinate represents the end of the sample, and the leftmost point on that colored line represents the start of the sample. In this case, the array from which samples are taken is [2, 3, -1, -20, 5, 10].
The longest increasing subsequence problem is closely related to the longest common subsequence problem, which has a quadratic time dynamic programming solution: the longest increasing subsequence of a sequence is the longest common subsequence of and , where is the result of sorting.
Given a function that accepts an array, a range query (,) on an array = [,..,] takes two indices and and returns the result of when applied to the subarray [, …,].For example, for a function that returns the sum of all values in an array, the range query (,) returns the sum of all values in the range [,].