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  2. Multidimensional assignment problem - Wikipedia

    en.wikipedia.org/wiki/Multidimensional...

    This problem can be seen as a generalization of the linear assignment problem. [2] In words, the problem can be described as follows: An instance of the problem has a number of agents (i.e., cardinality parameter) and a number of job characteristics (i.e., dimensionality parameter) such as task, machine, time interval, etc. For example, an ...

  3. Physics-informed neural networks - Wikipedia

    en.wikipedia.org/wiki/Physics-informed_neural...

    A general nonlinear partial differential equation can be: + [;] =,, [,] where (,) denotes the solution, [;] is a nonlinear operator parameterized by , and is a subset of .This general form of governing equations summarizes a wide range of problems in mathematical physics, such as conservative laws, diffusion process, advection-diffusion systems, and kinetic equations.

  4. Distributed artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Distributed_artificial...

    Parallel problem solving: mainly deals with how classic artificial intelligence concepts can be modified, so that multiprocessor systems and clusters of computers can be used to speed up calculation. Distributed problem solving (DPS): the concept of agent , autonomous entities that can communicate with each other, was developed to serve as an ...

  5. Wahba's problem - Wikipedia

    en.wikipedia.org/wiki/Wahba's_problem

    This is an alternative formulation of the Orthogonal Procrustes problem (consider all the vectors multiplied by the square-roots of the corresponding weights as columns of two matrices with N columns to obtain the alternative formulation). An elegant derivation of the solution on one and a half page can be found in. [3]

  6. Stochastic gradient descent - Wikipedia

    en.wikipedia.org/wiki/Stochastic_gradient_descent

    TensorFlow and PyTorch, by far the most popular machine learning libraries, [20] as of 2023 largely only include Adam-derived optimizers, as well as predecessors to Adam such as RMSprop and classic SGD. PyTorch also partially supports Limited-memory BFGS, a line-search method, but only for single-device setups without parameter groups. [19] [21]

  7. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    The torch package also simplifies object-oriented programming and serialization by providing various convenience functions which are used throughout its packages. The torch.class(classname, parentclass) function can be used to create object factories ().

  8. Open-source artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Open-source_artificial...

    Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]

  9. PyTorch Lightning - Wikipedia

    en.wikipedia.org/wiki/PyTorch_Lightning

    PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.