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  2. Change-making problem - Wikipedia

    en.wikipedia.org/wiki/Change-making_problem

    The following is a dynamic programming implementation (with Python 3) which uses a matrix to keep track of the optimal solutions to sub-problems, and returns the minimum number of coins, or "Infinity" if there is no way to make change with the coins given. A second matrix may be used to obtain the set of coins for the optimal solution.

  3. LeetCode - Wikipedia

    en.wikipedia.org/wiki/LeetCode

    LeetCode LLC, doing business as LeetCode, is an online platform for coding interview preparation. The platform provides coding and algorithmic problems intended for users to practice coding . [ 1 ] LeetCode has gained popularity among job seekers in the software industry and coding enthusiasts as a resource for technical interviews and coding ...

  4. 2-satisfiability - Wikipedia

    en.wikipedia.org/wiki/2-satisfiability

    The median of any three solutions is formed by setting each variable to the value it holds in the majority of the three solutions. This median always forms another solution to the instance. [32] Feder (1994) describes an algorithm for efficiently listing all solutions to a given 2-satisfiability instance, and for solving several related ...

  5. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    The algorithm described by Durstenfeld is more efficient than that given by Fisher and Yates: whereas a naïve computer implementation of Fisher and Yates' method would spend needless time counting the remaining numbers in step 3 above, Durstenfeld's solution is to move the "struck" numbers to the end of the list by swapping them with the last ...

  6. 145 (number) - Wikipedia

    en.wikipedia.org/wiki/145_(number)

    Although composite, 145 is a Fermat pseudoprime in sixteen bases with b < 145. In four of those bases, it is a strong pseudoprime: 1, 12, 17, and 144. the Mertens function returns 0. [1] 145 is a pentagonal number [2] and a centered square number. [3]

  7. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster.

  8. Miller–Rabin primality test - Wikipedia

    en.wikipedia.org/wiki/Miller–Rabin_primality_test

    Using repeated squaring, the running time of this algorithm is O(k n 3), for an n-digit number, and k is the number of rounds performed; thus this is an efficient, polynomial-time algorithm. FFT -based multiplication, for example the Schönhage–Strassen algorithm , can decrease the running time to O( k n 2 log n log log n ) = Õ ( k n 2 ) .

  9. Catalan number - Wikipedia

    en.wikipedia.org/wiki/Catalan_number

    In Figure 3, the black dot indicates the point where the path first crosses the diagonal. The black edge is X, and we place the last lattice point of the red portion in the top-right corner, and the first lattice point of the green portion in the bottom-left corner, and place X accordingly, to make a new path, shown in the second diagram. Figure 3.