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  2. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    In this case, the array from which samples are taken is [2, 3, -1, -20, 5, 10]. In computer science, the maximum sum subarray problem, also known as the maximum segment sum problem, is the task of finding a contiguous subarray with the largest sum, within a given one-dimensional array A [1...n] of numbers. It can be solved in time and space.

  3. Talk:Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Talk:Maximum_subarray_problem

    Applying the algorithm as shown in the page, I get a maximum subarray of 11, whereas the maximum subarray should be 13 (3 + 10) — Preceding unsigned comment added by 187.194.146.244 17:31, 16 November 2013 (UTC) (Scratch previous comment, the algorithm is correct) The solution given in python is incorrect. Please remove the code.

  4. Joseph Born Kadane - Wikipedia

    en.wikipedia.org/wiki/Joseph_Born_Kadane

    Giovanni Parmigiani. Joseph "Jay" Born Kadane (born January 10, 1941) is the Leonard J. Savage University Professor of Statistics, Emeritus in the Department of Statistics and Social and Decision Sciences at Carnegie Mellon University. Kadane is one of the early proponents of Bayesian statistics, particularly the subjective Bayesian philosophy.

  5. Longest increasing subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_increasing_subsequence

    one of the longest increasing subsequences is. 0, 2, 6, 9, 11, 15. This subsequence has length six; the input sequence has no seven-member increasing subsequences. The longest increasing subsequence in this example is not the only solution: for instance, are other increasing subsequences of equal length in the same input sequence.

  6. Lucas–Kanade method - Wikipedia

    en.wikipedia.org/wiki/Lucas–Kanade_method

    In computer vision, the Lucas–Kanade method is a widely used differential method for optical flow estimation developed by Bruce D. Lucas and Takeo Kanade.It assumes that the flow is essentially constant in a local neighbourhood of the pixel under consideration, and solves the basic optical flow equations for all the pixels in that neighbourhood, by the least squares criterion.

  7. Knapsack problem - Wikipedia

    en.wikipedia.org/wiki/Knapsack_problem

    Definition. The most common problem being solved is the 0-1 knapsack problem, which restricts the number of copies of each kind of item to zero or one. Given a set of items numbered from 1 up to , each with a weight and a value , along with a maximum weight capacity , subject to and . Here represents the number of instances of item to include ...

  8. Ruzzo–Tompa algorithm - Wikipedia

    en.wikipedia.org/wiki/Ruzzo–Tompa_algorithm

    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]

  9. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    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. Moreover, some restricted variants of it are NP-complete too ...