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  2. Computational complexity of matrix multiplication - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    C [i][j] = C [i][j] + A [i][k]* B [k][j] output C (as A*B) This algorithm requires, in the worst case, ⁠ ⁠ multiplications of scalars and ⁠ ⁠ additions for computing the product of two square n×n matrices. Its computational complexity is therefore ⁠ ⁠, in a model of computation where field operations (addition and multiplication ...

  3. Millennium Prize Problems - Wikipedia

    en.wikipedia.org/wiki/Millennium_Prize_Problems

    t. e. The Millennium Prize Problems are seven well-known complex mathematical problems selected by the Clay Mathematics Institute in 2000. The Clay Institute has pledged a US $1 million prize for the first correct solution to each problem. The Clay Mathematics Institute officially designated the title Millennium Problem for the seven unsolved ...

  4. Matrix multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication...

    The definition of matrix multiplication is that if C = AB for an n × m matrix A and an m × p matrix B, then C is an n × p matrix with entries. From this, a simple algorithm can be constructed which loops over the indices i from 1 through n and j from 1 through p, computing the above using a nested loop: Input: matrices A and B.

  5. Collatz conjecture - Wikipedia

    en.wikipedia.org/wiki/Collatz_conjecture

    For instance, the first counterexample must be odd because f(2n) = n, smaller than 2n; and it must be 3 mod 4 because f 2 (4n + 1) = 3n + 1, smaller than 4n + 1. For each starting value a which is not a counterexample to the Collatz conjecture, there is a k for which such an inequality holds, so checking the Collatz conjecture for one starting ...

  6. P versus NP problem - Wikipedia

    en.wikipedia.org/wiki/P_versus_NP_problem

    The P versus NP problem is a major unsolved problem in theoretical computer science. Informally, it asks whether every problem whose solution can be quickly verified can also be quickly solved. Here, quickly means an algorithm that solves the task and runs in polynomial time exists, meaning the task completion time is bounded above by a ...

  7. How to Solve It - Wikipedia

    en.wikipedia.org/wiki/How_to_Solve_It

    Genre. Mathematics, problem solving. Publication date. 1945. ISBN. 9780691164076. How to Solve It (1945) is a small volume by mathematician George Pólya, describing methods of problem solving. [1] This book has remained in print continually since 1945.

  8. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    An algorithm is said to be exponential time, if T(n) is upper bounded by 2 poly(n), where poly(n) is some polynomial in n. More formally, an algorithm is exponential time if T(n) is bounded by O(2 n k) for some constant k. Problems which admit exponential time algorithms on a deterministic Turing machine form the complexity class known as EXP.

  9. Moore–Penrose inverse - Wikipedia

    en.wikipedia.org/wiki/Moore–Penrose_inverse

    Moore–Penrose inverse. In mathematics, and in particular linear algebra, the Moore–Penrose inverse ⁠ ⁠ of a matrix ⁠ ⁠, often called the pseudoinverse, is the most widely known generalization of the inverse matrix. [1] It was independently described by E. H. Moore in 1920, [2] Arne Bjerhammar in 1951, [3] and Roger Penrose in 1955. [4]

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