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  2. Benders decomposition - Wikipedia

    en.wikipedia.org/wiki/Benders_decomposition

    Because the feasible space only shrinks as information is added, the objective value for the master function provides a lower bound on the objective function of the overall problem. Benders Decomposition is applicable to problems with a largely block-diagonal structure.

  3. Landauer's principle - Wikipedia

    en.wikipedia.org/wiki/Landauer's_principle

    Landauer's principle is a physical principle pertaining to a lower theoretical limit of energy consumption of computation.It holds that an irreversible change in information stored in a computer, such as merging two computational paths, dissipates a minimum amount of heat to its surroundings. [1]

  4. Binary search - Wikipedia

    en.wikipedia.org/wiki/Binary_search

    Binary search Visualization of the binary search algorithm where 7 is the target value Class Search algorithm Data structure Array Worst-case performance O (log n) Best-case performance O (1) Average performance O (log n) Worst-case space complexity O (1) Optimal Yes In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search ...

  5. Cramér–Rao bound - Wikipedia

    en.wikipedia.org/wiki/Cramér–Rao_bound

    [6] [7] It is also known as Fréchet-Cramér–Rao or Fréchet-Darmois-Cramér-Rao lower bound. It states that the precision of any unbiased estimator is at most the Fisher information; or (equivalently) the reciprocal of the Fisher information is a lower bound on its variance.

  6. Limited-memory BFGS - Wikipedia

    en.wikipedia.org/wiki/Limited-memory_BFGS

    The L-BFGS-B algorithm extends L-BFGS to handle simple box constraints (aka bound constraints) on variables; that is, constraints of the form l i ≤ x i ≤ u i where l i and u i are per-variable constant lower and upper bounds, respectively (for each x i, either or both bounds may be omitted).

  7. Circuit complexity - Wikipedia

    en.wikipedia.org/wiki/Circuit_complexity

    Proving lower bounds on size of Boolean circuits computing explicit Boolean functions is a popular approach to separating complexity classes. For example, a prominent circuit class P/poly consists of Boolean functions computable by circuits of polynomial size.

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  9. Branch and bound - Wikipedia

    en.wikipedia.org/wiki/Branch_and_bound

    The following is the skeleton of a generic branch and bound algorithm for minimizing an arbitrary objective function f. [3] To obtain an actual algorithm from this, one requires a bounding function bound, that computes lower bounds of f on nodes of the search tree, as well as a problem-specific branching rule.