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  2. Linear-nonlinear-Poisson cascade model - Wikipedia

    en.wikipedia.org/wiki/Linear-nonlinear-Poisson...

    The parameters of the LNP model consist of the linear filters {} and the nonlinearity . The estimation problem (also known as the problem of neural characterization) is the problem of determining these parameters from data consisting of a time-varying stimulus and the set of observed spike times. Techniques for estimating the LNP model ...

  3. List of NP-complete problems - Wikipedia

    en.wikipedia.org/wiki/List_of_NP-complete_problems

    The problem for graphs is NP-complete if the edge lengths are assumed integers. The problem for points on the plane is NP-complete with the discretized Euclidean metric and rectilinear metric. The problem is known to be NP-hard with the (non-discretized) Euclidean metric. [3]: ND22, ND23

  4. Assignment problem - Wikipedia

    en.wikipedia.org/wiki/Assignment_problem

    Worked example of assigning tasks to an unequal number of workers using the Hungarian method. The assignment problem is a fundamental combinatorial optimization problem. In its most general form, the problem is as follows: The problem instance has a number of agents and a number of tasks.

  5. Linear bottleneck assignment problem - Wikipedia

    en.wikipedia.org/wiki/Linear_bottleneck...

    The formal definition of the bottleneck assignment problem is Given two sets, A and T, together with a weight function C : A × T → R. Find a bijection f : A → T such that the cost function: (, ()) is minimized.

  6. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    The SciPy scientific library, for instance, uses HiGHS as its LP solver [13] from release 1.6.0 [14] and the HiGHS MIP solver for discrete optimization from release 1.9.0. [15] As well as offering an interface to HiGHS, the JuMP modelling language for Julia [ 16 ] also describes the specific use of HiGHS in its user documentation. [ 17 ]

  7. Karp's 21 NP-complete problems - Wikipedia

    en.wikipedia.org/wiki/Karp's_21_NP-complete_problems

    In computational complexity theory, Karp's 21 NP-complete problems are a set of computational problems which are NP-complete.In his 1972 paper, "Reducibility Among Combinatorial Problems", [1] Richard Karp used Stephen Cook's 1971 theorem that the boolean satisfiability problem is NP-complete [2] (also called the Cook-Levin theorem) to show that there is a polynomial time many-one reduction ...

  8. Longest path problem - Wikipedia

    en.wikipedia.org/wiki/Longest_path_problem

    In this decision problem, the input is a graph G and a number k; the desired output is yes if G contains a path of k or more edges, and no otherwise. [1] If the longest path problem could be solved in polynomial time, it could be used to solve this decision problem, by finding a longest path and then comparing its length to the number k ...

  9. Single-machine scheduling - Wikipedia

    en.wikipedia.org/wiki/Single-machine_scheduling

    Single-machine scheduling or single-resource scheduling or Dhinchak Pooja is an optimization problem in computer science and operations research.We are given n jobs J 1, J 2, ..., J n of varying processing times, which need to be scheduled on a single machine, in a way that optimizes a certain objective, such as the throughput.