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  2. Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Huffman_coding

    In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression.The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Huffman while he was a Sc.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes".

  3. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    A greedy algorithm is used to construct a Huffman tree during Huffman coding where it finds an optimal solution. In decision tree learning, greedy algorithms are commonly used, however they are not guaranteed to find the optimal solution. One popular such algorithm is the ID3 algorithm for decision tree construction.

  4. LZ77 and LZ78 - Wikipedia

    en.wikipedia.org/wiki/LZ77_and_LZ78

    BTLZ is an LZ78-based algorithm that was developed for use in real-time communications systems (originally modems) and standardized by CCITT/ITU as V.42bis. When the trie-structured dictionary is full, a simple re-use/recovery algorithm is used to ensure that the dictionary can keep adapting to changing data. A counter cycles through the ...

  5. Change-making problem - Wikipedia

    en.wikipedia.org/wiki/Change-making_problem

    The change-making problem addresses the question of finding the minimum number of coins (of certain denominations) that add up to a given amount of money. It is a special case of the integer knapsack problem, and has applications wider than just currency. It is also the most common variation of the coin change problem, a general case of ...

  6. Heuristic (computer science) - Wikipedia

    en.wikipedia.org/wiki/Heuristic_(computer_science)

    For other uses, see Heuristic (disambiguation). In mathematical optimization and computer science, heuristic (from Greek εὑρίσκω "I find, discover" [1]) is a technique designed for problem solving more quickly when classic methods are too slow for finding an exact or approximate solution, or when classic methods fail to find any exact ...

  7. Maximum coverage problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_coverage_problem

    The maximum coverage problem is a classical question in computer science, computational complexity theory, and operations research. It is a problem that is widely taught in approximation algorithms. As input you are given several sets and a number . The sets may have some elements in common. You must select at most of these sets such that the ...

  8. Greedy coloring - Wikipedia

    en.wikipedia.org/wiki/Greedy_coloring

    Greedy coloring. Two greedy colorings of the same crown graph using different vertex orders. The right example generalises to 2-colorable graphs with n vertices, where the greedy algorithm expends n/2 colors. In the study of graph coloring problems in mathematics and computer science, a greedy coloring or sequential coloring[1] is a coloring of ...

  9. Optimal substructure - Wikipedia

    en.wikipedia.org/wiki/Optimal_substructure

    This property is used to determine the usefulness of greedy algorithms for a problem. [1] Typically, a greedy algorithm is used to solve a problem with optimal substructure if it can be proven by induction that this is optimal at each step. [1] Otherwise, provided the problem exhibits overlapping subproblems as well, divide-and-conquer methods ...