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Articles, 2 registres trobats Documents de recerca, 1 registres trobats

Articles	2 registres trobats

12 p, 562.9 KB

On proving existence of feasible points in equality constrained optimization problems / Kearfott, R. Baker
Various algorithms can compute approximate feasible points or approximate solutions to equality and bound constrained optimization problems. In exhaustive search algorithms for global optimizers and other contexts, it is of interest to construct bounds around such approximate feasible points, then to verify (computationally but rigorously) that an actual feasible point exists within these bounds. [...]
1998
Mathematical Programming, vol. 83 n. 1 (1998) p. 89-100

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19 p, 845.2 KB

A trust region method for minimization of nonsmooth functions with linear constraints / Martínez, José Mario ; Moretti, Antonio Carlos
We introduce a trust region algorithm for minimization of nonsmooth functions with linear constraints. At each iteration, the objective function is approximated by a model function that satisfies a set of assumptions stated recently by Qi and Sun in the context of unconstrained nonsmooth optimization. [...]
1997
Mathematical Programming, vol. 76 n. 3 (1997) p. 431-449

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Documents de recerca	1 registres trobats

26.9 MB

Efficient Neural Network Inference for Resource Constrained Devices / Borrego Carazo, Juan ; Carrabina Bordoll, Jordi, dir. ; Castells-Rufas, David, dir.
Els avenços de la darrera dècada en l'aprenentatge profund han suposat un gran salt en els resultats d'última generació pel que fa a tasques com la classificació d'imatges, la traducció d'idiomes i moltes altres. [...]
Los avances de la última década en el aprendizaje profundo han supuesto un gran salto en los resultados del estado del arte en tareas como la clasificación de imágenes, la traducción de idiomas y muchas otras. [...]
Last decade advances in deep learning have supposed a great leap in state-of-the-art results with regard to tasks such as image classification, language translation, and many others. However, with such success, there has been a related increase in model complexity and size, which has incremented the hardware requirements both for training and inference (both generally and initially limited to GPUs). [...]
2022

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