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  2. Sequential quadratic programming - Wikipedia

    en.wikipedia.org/wiki/Sequential_quadratic...

    Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization which may be considered a quasi-Newton method.SQP methods are used on mathematical problems for which the objective function and the constraints are twice continuously differentiable, but not necessarily convex.

  3. Commercial National Security Algorithm Suite - Wikipedia

    en.wikipedia.org/wiki/Commercial_National...

    The Commercial National Security Algorithm Suite (CNSA) is a set of cryptographic algorithms promulgated by the National Security Agency as a replacement for NSA Suite B Cryptography algorithms. It serves as the cryptographic base to protect US National Security Systems information up to the top secret level, while the NSA plans for a ...

  4. Stochastic approximation - Wikipedia

    en.wikipedia.org/wiki/Stochastic_approximation

    Stochastic approximation methods are a family of iterative methods typically used for root-finding problems or for optimization problems. The recursive update rules of stochastic approximation methods can be used, among other things, for solving linear systems when the collected data is corrupted by noise, or for approximating extreme values of functions which cannot be computed directly, but ...

  5. Introduction to Algorithms - Wikipedia

    en.wikipedia.org/wiki/Introduction_to_Algorithms

    Introduction to Algorithms is a book on computer programming by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The book is described by its publisher as "the leading algorithms text in universities worldwide as well as the standard reference for professionals". [ 1 ]

  6. The Art of Computer Programming - Wikipedia

    en.wikipedia.org/wiki/The_Art_of_Computer...

    The offer of a so-called Knuth reward check worth "one hexadecimal dollar" (100 HEX base 16 cents, in decimal, is $2.56) for any errors found, and the correction of these errors in subsequent printings, has contributed to the highly polished and still-authoritative nature of the work, long after its first publication.

  7. Sinkhorn's theorem - Wikipedia

    en.wikipedia.org/wiki/Sinkhorn's_theorem

    Sinkhorn and Knopp presented this algorithm and analyzed its convergence. [3] This is essentially the same as the Iterative proportional fitting algorithm, well known in survey statistics. Analogues and extensions

  8. Gale–Shapley algorithm - Wikipedia

    en.wikipedia.org/wiki/Gale–Shapley_algorithm

    The algorithm can be implemented to run in time quadratic in the number of participants, and linear in the size of the input to the algorithm. The stable matching problem, and the Gale–Shapley algorithm solving it, have widespread real-world applications, including matching American medical students to residencies and French university ...

  9. Lattice problem - Wikipedia

    en.wikipedia.org/wiki/Lattice_problem

    Lattice reduction algorithms aim, given a basis for a lattice, to output a new basis consisting of relatively short, nearly orthogonal vectors. The Lenstra–Lenstra–Lovász lattice basis reduction algorithm (LLL) was an early efficient algorithm for this problem which could output an almost reduced lattice basis in polynomial time. [33]