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  2. Longest alternating subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_Alternating...

    The longest alternating subsequence problem has also been studied in the setting of online algorithms, in which the elements of are presented in an online fashion, and a decision maker needs to decide whether to include or exclude each element at the time it is first presented, without any knowledge of the elements that will be presented in the future, and without the possibility of recalling ...

  3. Longest increasing subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_increasing_subsequence

    The longest increasing subsequence has also been studied in the setting of online algorithms, in which the elements of a sequence of independent random variables with continuous distribution – or alternatively the elements of a random permutation – are presented one at a time to an algorithm that must decide whether to include or exclude ...

  4. Longest common subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_common_subsequence

    A longest common subsequence (LCS) is the longest subsequence common to all sequences in a set of sequences (often just two sequences). It differs from the longest common substring : unlike substrings, subsequences are not required to occupy consecutive positions within the original sequences.

  5. Longest path problem - Wikipedia

    en.wikipedia.org/wiki/Longest_path_problem

    In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.

  6. Hunt–Szymanski algorithm - Wikipedia

    en.wikipedia.org/wiki/Hunt–Szymanski_algorithm

    The above algorithm has worst-case time and space complexities of O(mn) (see big O notation), where m is the number of elements in sequence A and n is the number of elements in sequence B. The Hunt–Szymanski algorithm modifies this algorithm to have a worst-case time complexity of O(mn log m) and space complexity of O(mn), though it regularly ...

  7. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    Hence, one can easily formulate the solution for finding shortest paths in a recursive manner, which is what the Bellman–Ford algorithm or the Floyd–Warshall algorithm does. Overlapping sub-problems means that the space of sub-problems must be small, that is, any recursive algorithm solving the problem should solve the same sub-problems ...

  8. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.

  9. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    This algorithm runs in () time. The array L stores the length of the longest common suffix of the prefixes S[1..i] and T[1..j] which end at position i and j, respectively. The variable z is used to hold the length of the longest common substring found so far.